A. Lauritzen, M. von Euler-Chelpin, E. Lynge, I. Vejborg, M. Nielsen, N. Karssemeijer and M. Lillholm, "Robust cross-vendor mammographic texture models using augmentation-based domain adaptation for long-term breast cancer risk",
Journal of Medical Imaging,
2023;10.
R. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen and R. Mann, "Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRI",
Diagnostics,
2022;12:1690.
A. Lauritzen, A. Rodríguez-Ruiz, M. von Euler-Chelpin, E. Lynge, I. Vejborg, M. Nielsen, N. Karssemeijer and M. Lillholm, "An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload",
Radiology,
2022;304:41-49.
A. Wanders, W. Mees, P. Bun, N. Janssen, A. Rodríguez-Ruiz, M. Dalmış, N. Karssemeijer, C. van Gils, I. Sechopoulos, R. Mann and C. van Rooden, "Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms",
Radiology,
2022;303:269-275.
L. Kerschke, S. Weigel, A. Rodriguez-Ruiz, N. Karssemeijer and W. Heindel, "Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance",
European Radiology,
2021;32:842-852.
S. van Winkel, A. Rodríguez-Ruiz, L. Appelman, A. Gubern-Mérida, N. Karssemeijer, J. Teuwen, A. Wanders, I. Sechopoulos and R. Mann, "Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study",
European Radiology,
2021;31:8682-8691.
S. Veenhuizen, S. de Lange, M. Bakker, R. Pijnappel, R. Mann, E. Monninkhof, M. Emaus, P. de Koekkoek-Doll, R. Bisschops, M. Lobbes, M. de Jong, K. Duvivier, J. Veltman, N. Karssemeijer, H. de Koning, P. van Diest, W. Mali, M. van den Bosch, C. van Gils, W. Veldhuis, C. van Gils, M. Bakker, S. de Lange, S. Veenhuizen, W. Veldhuis, R. Pijnappel, M. Emaus, P. Peeters, E. Monninkhof, M. Fernandez-Gallardo, W. Mali, M. van den Bosch, P. van Diest, R. Mann, R. Mus, M. Imhof-Tas, N. Karssemeijer, C. Loo, P. de Koekkoek-Doll, H. Winter-Warnars, R. Bisschops, M. Kock, R. Storm, P. van der Valk, M. Lobbes, S. Gommers, M. Lobbes, M. de Jong, M. Rutten, K. Duvivier, P. de Graaf, J. Veltman, R. Bourez, H. de Koning and F. the Group, "Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial",
Radiology,
2021;299:278-286.
W. Sanderink, J. Teuwen, L. Appelman, L. Moy, L. Heacock, E. Weiland, N. Karssemeijer, P. Baltzer, I. Sechopoulos and R. Mann, "Comparison of simultaneous multi-slice single-shot DWI to readout-segmented DWI for evaluation of breast lesions at 3T MRI",
European Journal of Radiology,
2021;138:109626.
W. Sanderink, L. Strobbe, P. Bult, M. Schlooz-Vries, S. Lardenoije, D. Venderink, I. Sechopoulos, N. Karssemeijer, W. Vreuls and R. Mann, "Minimally invasive breast cancer excision using the breast lesion excision system under ultrasound guidance",
Breast Cancer Research and Treatment,
2020;184:37-43.
W. Sanderink, M. Caballo, L. Strobbe, P. Bult, W. Vreuls, D. Venderink, I. Sechopoulos, N. Karssemeijer and R. Mann, "Reliability of MRI tumor size measurements for minimal invasive treatment selection in small breast cancers",
European Journal of Surgical Oncology,
2020;46:1463-1470.
J. van Zelst, T. Tan, R. Mann and N. Karssemeijer, "Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software",
Acta Radiologica,
2020;61(3):312-320.
E. García, Y. Diez, A. Oliver, N. Karssemeijer, J. Martí, R. Martí and O. Diaz, "Evaluation of elastic parameters for breast compression using a MRI-mammography registration approach",
15th International Workshop on Breast Imaging (IWBI2020),
2020.
C. Balta, A. Rodriguez-Ruiz, C. Mieskes, N. Karssemeijer and S. Heywang-Köbrunner, "Going from double to single reading for screening exams labeled as likely normal by AI: what is the impact?",
15th International Workshop on Breast Imaging (IWBI2020),
2020.
W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann, "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions",
ISMRM Benelux,
2020.
M. Balkenhol, "Tissue-based biomarker assessment for predicting prognosis of triple negative breast cancer: the additional value of artificial intelligence",
PhD thesis,
2020.
M. Bakker, S. de Lange, R. Pijnappel, R. Mann, P. Peeters, E. Monninkhof, M. Emaus, C. Loo, R. Bisschops, M. Lobbes, M. de Jong, K. Duvivier, J. Veltman, N. Karssemeijer, H. de Koning, P. van Diest, W. Mali, M. van den Bosch, W. Veldhuis, C. van Gils and D. Group, "Supplemental MRI Screening for Women with Extremely Dense Breast Tissue",
New England Journal of Medicine,
2019;381(22):2091-2102.
M. Mullooly, B. Ehteshami Bejnordi, R. Pfeiffer, S. Fan, M. Palakal, M. Hada, P. Vacek, D. Weaver, J. Shepherd, B. Fan, A. Mahmoudzadeh, J. Wang, S. Malkov, J. Johnson, S. Herschorn, B. Sprague, S. Hewitt, L. Brinton, N. Karssemeijer, J. van der Laak, A. Beck, M. Sherman and G. Gierach, "Application of convolutional neural networks to breast biopsies to delineate tissue correlates of mammographic breast density",
NPJ Breast Cancer,
2019;5:43.
C. Balta, R. Bouwman, M. Broeders, N. Karssemeijer, W. Veldkamp, I. Sechopoulos and R. van Engen, "Optimization of the difference-of-Gaussian channel sets for the channelized Hotelling observer",
Journal of Medical Imaging,
2019;6(3):035501.
S. Saadatmand, H. Geuzinge, E. Rutgers, R. Mann, D. de van Roy Zuidewijn, H. Zonderland, R. Tollenaar, M. Lobbes, M. Ausems, M. van 't Riet, M. Hooning, I. Mares-Engelberts, E. Luiten, E. Heijnsdijk, C. Verhoef, N. Karssemeijer, J. Oosterwijk, I. Obdeijn, H. de Koning, M. Tilanus-Linthorst and F. study group, "MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial",
Lancet Oncology,
2019;20(8):1136-1147.
W. Sanderink, B. Laarhuis, L. Strobbe, I. Sechopoulos, P. Bult, N. Karssemeijer and R. Mann, "A systematic review on the use of the breast lesion excision system in breast disease",
Insights into Imaging,
2019;10(1):49.
S. Vreemann, M. Dalmis, P. Bult, N. Karssemeijer, M. Broeders, A. Gubern-Mérida and R. Mann, "Amount of fibroglandular tissue FGT and background parenchymal enhancement BPE in relation to breast cancer risk and false positives in a breast MRI screening program",
European Radiology,
2019;29:4678-4690.
G. Napolitano, E. Lynge, M. Lillholm, I. Vejborg, C. van Gils, M. Nielsen and N. Karssemeijer, "Change in mammographic density across birth cohorts of Dutch breast cancer screening participants",
International Journal of Cancer,
2019;145(11):2954-2962.
M. Dalmis, A. Gubern-Mérida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann and J. Teuwen, "Artificial Intelligence Based Classification of Breast Lesions Imaged With a Multi-Parametric Breast MRI Protocol With ultrafast DCE-MRI, T2 and DWI",
Investigative Radiology,
2019;56(6):325-332.
C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "Can a channelized Hotelling observer assess image quality in acquired mammographic images of an anthropomorphic breast phantom including image processing?",
Medical Physics,
2019;46:714-725.
M. Kallenberg, D. Vanegas Camargo, M. Birhanu, A. Gubern-Mérida and N. Karssemeijer, "A deep learning method for volumetric breast density estimation from processed full field digital mammograms",
Medical Imaging 2019: Computer-Aided Diagnosis,
2019.
W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann, "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions",
Annual Meeting of the International Society for Magnetic Resonance in Medicine,
2019.
S. Vreemann, J. van Zelst, M. Schlooz-Vries, P. Bult, N. Hoogerbrugge, N. Karssemeijer, A. Gubern-Merida and R. Mann, "The added value of mammography in different age-groups of women with and without BRCA mutation screened with breast MRI",
Breast Cancer Research,
2018;20(1):84.
D. Tellez, M. Balkenhol, I. Otte-Holler, R. van de Loo, R. Vogels, P. Bult, C. Wauters, W. Vreuls, S. Mol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks",
IEEE Transactions on Medical Imaging,
2018;37(9):2126 - 2136.
A. Bria, C. Marrocco, L. Borges, M. Molinara, A. Marchesi, J. Mordang, N. Karssemeijer and F. Tortorella, "Improving the Automated Detection of Calcifications using Adaptive Variance Stabilization",
IEEE Transactions on Medical Imaging,
2018;37(8):1857-1864.
J. van Zelst, S. Vreemann, H. Witt, A. Gubern-Merida, M. Dorrius, K. Duvivier, S. Lardenoije-Broker, M. Lobbes, C. Loo, W. Veldhuis, J. Veltman, D. Drieling, N. Karssemeijer and R. Mann, "Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening",
Investigative Radiology,
2018;53(10):579-586.
B. Ehteshami Bejnordi, M. Mullooly, R. Pfeiffer, S. Fan, P. Vacek, D. Weaver, S. Herschorn, L. Brinton, B. van Ginneken, N. Karssemeijer, A. Beck, G. Gierach, J. van der Laak and M. Sherman, "Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies",
Modern Pathology,
2018;31(10):1502-1512.
S. de Lange, M. Bakker, E. Monninkhof, P. Peeters, P. de Koekkoek-Doll, R. Mann, M. Rutten, R. Bisschops, J. Veltman, K. Duvivier, M. Lobbes, H. de Koning, N. Karssemeijer, R. Pijnappel, W. Veldhuis and C. van Gils, "Reasons for (non)participation in supplemental population-based MRI breast screening for women with extremely dense breasts",
Clinical Radiology,
2018;73(8):759e1-759e9.
J. Wanders, C. van Gils, N. Karssemeijer, K. Holland, M. Kallenberg, P. Peeters, M. Nielsen and M. Lillholm, "The combined effect of mammographic texture and density on breast cancer risk: a cohort study",
Breast Cancer Research,
2018;20.
J. van Zelst, T. Tan, P. Clauser, A. Domingo, M. Dorrius, D. Drieling, M. Golatta, F. Gras, M. de Jong, R. Pijnappel, M. Rutten, N. Karssemeijer and R. Mann, "Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts",
European Radiology,
2018;28(7):2996-3006.
S. Vreemann, A. Gubern-Merida, S. Lardenoije, P. Bult, N. Karssemeijer, K. Pinker and R. Mann, "The frequency of missed breast cancers in women participating in a high-risk MRI screening program",
Breast Cancer Research and Treatment,
2018;169(2):323-331.
S. Vreemann, A. Gubern-Mérida, C. Borelli, P. Bult, N. Karssemeijer and R. Mann, "The correlation of background parenchymal enhancement in the contralateral breast with patient and tumor characteristics of MRI-screen detected breast cancers",
PLoS One,
2018;13(1):e0191399.
M. Dalmis, S. Vreemann, T. Kooi, R. Mann, N. Karssemeijer and A. Gubern-Merida, "Fully automated detection of breast cancer in screening MRI using convolutional neural networks",
Journal of Medical Imaging,
2018;5(1):014502.
A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R. Bouwman, R. van Engen, N. Karssemeijer, R. Mann, A. Gubern-Merida and I. Sechopoulos, "New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers",
Acta Radiologica,
2018;59(9):1051-1059.
A. Rodriguez-Ruiz, A. Gubern-Merida, M. Imhof-Tas, S. Lardenoije, A. Wanders, I. Andersson, S. Zackrisson, K. Lang, M. Dustler, N. Karssemeijer, R. Mann and I. Sechopoulos, "One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?",
European Radiology,
2018;28(5):1938-1948.
C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "A model observer study using acquired mammographic images of an anthropomorphic breast phantom",
Medical Physics,
2018;45(2):655-665.
J. Mordang, A. Gubern-Merida, A. Bria, F. Tortorella, R. Mann, M. Broeders, G. den Heeten and N. Karssemeijer, "The importance of early detection of calcifications associated with breast cancer in screening",
Breast Cancer Research and Treatment,
2018;167(2):451-458.
S. Vreemann, A. Gubern-Merida, M. Schlooz-Vries, P. Bult, C. van Gils, N. Hoogerbrugge, N. Karssemeijer and R. Mann, "Influence of Risk Category and Screening Round on the Performance of an MR Imaging and Mammography Screening Program in Carriers of the BRCA Mutation and Other Women at Increased Risk",
Radiology,
2018;286(2):443-451.
A. Bria, B. Savelli, C. Marrocco, J. Mordang, M. Molinara, N. Karssemeijer and F. Tortorella, "Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets",
14th International Workshop on Breast Imaging (IWBI 2018),
2018.
A. Rodriguez-Ruiz, R. van Engen, K. Michielsen, R. Bouwman, S. Vreemann, N. Karssemeijer, R. Mann and I. Sechopoulos, "How does wide-angle breast tomosynthesis depict calcifications in comparison to digital mammography? A retrospective observer study",
14th International Workshop on Breast Imaging (IWBI 2018),
2018.
M. Ghafoorian, J. Teuwen, R. Manniesing, F. de Leeuw, B. van Ginneken, N. Karssemeijer and B. Platel, "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR",
Medical Imaging,
2018;10574:105742U.
D. Tellez, M. Balkenhol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection",
Medical Imaging,
2018;10581.
C. Marrocco, A. Bria, V. Di Sano, L. Borges, B. Savelli, M. Molinara, J. Mordang, N. Karssemeijer and F. Tortorella, "Mammogram denoising to improve the calcification detection performance of convolutional nets",
14th International Workshop on Breast Imaging (IWBI 2018),
2018.
A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Merida and I. Sechopoulos, "Pectoral muscle segmentation in breast tomosynthesis with deep learning",
Medical Imaging,
2018.
A. Rodriguez-Ruiz, J. Mordang, N. Karssemeijer, I. Sechopoulos and R. Mann, "Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support?",
14th International Workshop on Breast Imaging (IWBI 2018),
2018.
B. Bejnordi, G. Zuidhof, M. Balkenhol, M. Hermsen, P. Bult, B. van Ginneken, N. Karssemeijer, G. Litjens and J. van der Laak, "Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images",
Journal of Medical Imaging,
2017;4(4):044504.
B. Ehteshami Bejnordi, M. Veta, P. van Diest, B. van Ginneken, N. Karssemeijer, G. Litjens, J. van der Laak, T. Consortium, M. Hermsen, Q. Manson, M. Balkenhol, O. Geessink, N. Stathonikos, M. van Dijk, P. Bult, F. Beca, A. Beck, D. Wang, A. Khosla, R. Gargeya, H. Irshad, A. Zhong, Q. Dou, Q. Li, H. Chen, H. Lin, P. Heng, C. Haß, E. Bruni, Q. Wong, U. Halici, M. Öner, R. Cetin-Atalay, M. Berseth, V. Khvatkov, A. Vylegzhanin, O. Kraus, M. Shaban, N. Rajpoot, R. Awan, K. Sirinukunwattana, T. Qaiser, Y. Tsang, D. Tellez, J. Annuscheit, P. Hufnagl, M. Valkonen, K. Kartasalo, L. Latonen, P. Ruusuvuori, K. Liimatainen, S. Albarqouni, B. Mungal, A. George, S. Demirci, N. Navab, S. Watanabe, S. Seno, Y. Takenaka, H. Matsuda, H. Ahmady Phoulady, V. Kovalev, A. Kalinovsky, V. Liauchuk, G. Bueno, M. Fernandez-Carrobles, I. Serrano, O. Deniz, D. Racoceanu and R. Venâncio, "Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer",
Journal of the American Medical Association,
2017;318(22):2199-2210.
K. Holland, I. Sechopoulos, R. Mann, G. den Heeten, C. van Gils and N. Karssemeijer, "Influence of breast compression pressure on the performance of population-based mammography screening",
Breast Cancer Research,
2017;19(1):126.
T. Kooi and N. Karssemeijer, "Classifying symmetrical differences and temporal change for the detection of malignant masses in mammography using deep neural networks",
Journal of Medical Imaging,
2017;4(4):International Society for Optics and Photonics.
E. Gray, A. Donten, N. Karssemeijer, C. van Gils, D. Evans, S. Astley and K. Payne, "Evaluation of a Stratified National Breast Screening Program in the United Kingdom: An Early Model-Based Cost-Effectiveness Analysis",
Value in Health,
2017;20:1100-1109.
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, C. Sánchez, G. Litjens, F. de Leeuw, B. van Ginneken, E. Marchiori and B. Platel, "Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities",
Scientific Reports,
2017;7(1):5110.
J. van Zelst, R. Mus, G. Woldringh, M. Rutten, P. Bult, S. Vreemann, M. de Jong, N. Karssemeijer, N. Hoogerbrugge and R. Mann, "Surveillance of Women with the BRCA1 or BRCA2 Mutation by Using Biannual Automated Breast US, MR Imaging, and Mammography",
Radiology,
2017;285(2):376-388.
J. Wanders, K. Holland, N. Karssemeijer, P. Peeters, W. Veldhuis, R. Mann and C. van Gils, "The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study",
Breast Cancer Research,
2017;19(1):67.
J. van Zelst, M. Balkenhol, T. Tan, M. Rutten, M. Imhof-Tas, P. Bult, N. Karssemeijer and R. Mann, "Sonographic Phenotypes of Molecular Subtypes of Invasive Ductal Cancer in Automated 3-D Breast Ultrasound",
Ultrasound in Medicine and Biology,
2017;43(9):1820-1828.
S. Vreemann, A. Rodriguez-Ruiz, D. Nickel, L. Heacock, L. Appelman, J. van Zelst, N. Karssemeijer, E. Weiland, M. Maas, L. Moy, B. Kiefer and R. Mann, "Compressed Sensing for Breast MRI: Resolving the Trade-Off Between Spatial and Temporal Resolution",
Investigative Radiology,
2017;52(10):574-582.
M. Ghafoorian, N. Karssemeijer, T. Heskes, M. Bergkamp, J. Wissink, J. Obels, K. Keizer, F. de Leeuw, B. Ginneken, E. Marchiori and B. Platel, "Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin",
NeuroImage: Clinical,
2017;14:391-399.
R. Mus, C. Borelli, P. Bult, E. Weiland, N. Karssemeijer, J. Barentsz, A. Gubern-Mérida, B. Platel and R. Mann, "Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions",
European Journal of Radiology,
2017;89:90-96.
J. van Zelst, T. Tan, B. Platel, M. de Jong, A. Steenbakkers, M. Mourits, A. Grivegnee, C. Borelli, N. Karssemeijer and R. Mann, "Improved cancer detection in automated breast ultrasound by radiologists using Computer Aided Detection",
European Journal of Radiology,
2017;89:54-59.
K. Holland, A. Gubern-Mérida, R. Mann and N. Karssemeijer, "Optimization of volumetric breast density estimation in digital mammograms",
Physics in Medicine and Biology,
2017;62(9):3779-3797.
J. Mordang, A. Gubern-Merida, A. Bria, F. Tortorella, G. den Heeten and N. Karssemeijer, "Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings",
Medical Physics,
2017;44(4):1390-1401.
K. Holland, C. van Gils, R. Mann and N. Karssemeijer, "Quantification of masking risk in screening mammography with volumetric breast density maps",
Breast Cancer Research and Treatment,
2017;162(3):541-548.
T. Kooi, B. van Ginneken, N. Karssemeijer and A. den Heeten, "Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network",
Medical Physics,
2017;44(3):1017-1027.
T. Mertzanidou, J. Hipwell, S. Reis, D. Hawkes, B. Bejnordi, M. Dalmis, S. Vreemann, B. Platel, J. van der Laak, N. Karssemeijer, M. Hermsen, P. Bult and R. Mann, "3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging",
Medical Physics,
2017;44(3):935-948.
M. Dalmis, G. Litjens, K. Holland, A. Setio, R. Mann, N. Karssemeijer and A. Gubern-Mérida, "Using deep learning to segment breast and fibroglandular tissue in MRI volumes",
Medical Physics,
2017;44(2):533-546.
J. Wanders, K. Holland, W. Veldhuis, R. Mann, R. Pijnappel, P. Peeters, C. van Gils and N. Karssemeijer, "Volumetric breast density affects performance of digital screening mammography",
Breast Cancer Research and Treatment,
2017;162(1):95-103.
T. Kooi, G. Litjens, B. van Ginneken, A. Gubern-Mérida, C. Sánchez, R. Mann, A. den Heeten and N. Karssemeijer, "Large scale deep learning for computer aided detection of mammographic lesions",
Medical Image Analysis,
2017;35:303-312.
T. Kooi and N. Karssemeijer, "Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks",
arXiv:1703.07715,
2017.
B. Bejnordi, J. Lin, B. Glass, M. Mullooly, G. Gierach, M. Sherman, N. Karssemeijer, J. van der Laak and A. Beck, "Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images",
IEEE International Symposium on Biomedical Imaging,
2017:929-932.
M. Ghafoorian, A. Mehrtash, T. Kapur, N. Karssemeijer, E. Marchiori, M. Pesteie, C. Guttmann, F. de Leeuw, C. Tempany, B. van Ginneken, A. Fedorov, P. Abolmaesumi, B. Platel and W. Wells, "Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation",
Medical Image Computing and Computer-Assisted Intervention,
2017;10435:516-524.
T. Kooi, J. Mordang and N. Karssemeijer, "Conditional Random Field Modelling of Interactions Between Findings in Mammography",
Medical Imaging,
2017;10133:101341E.
C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "Signal template generation from acquired mammographic images for the non-prewhitening model observer with eye-filter",
Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment,
2017.
A. Marchesi, A. Bria, C. Marrocco, M. Molinara, J. Mordang, F. Tortorella and N. Karssemeijer, "The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks",
2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS),
2017.
T. Kooi and N. Karssemeijer, "Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses",
Medical Imaging,
2017;10133:101341J.
J. Teuwen, M. Kallenberg, A. Gubern-Merida, A. Rodriguez-Ruiz, N. Karssemeijer and R. Mann, "Automated pre-selection of mammograms without abnormalities using deep learning",
Annual Meeting of the Radiological Society of North America,
2017.
A. Bria, C. Marrocco, A. Galdran, A. Campilho, A. Marchesi, J. Mordang, N. Karssemeijer, M. Molinara and F. Tortorella, "Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets",
Image Analysis and Processing - ICIAP 2017,
2017:288-298.
M. Ghafoorian, N. Karssemeijer, I. van Uden, F. de Leeuw, T. Heskes, E. Marchiori and B. Platel, "Automated Detection of White Matter Hyperintensities of All Sizes in Cerebral Small Vessel Disease",
Medical Physics,
2016;43(12):6246-6258.
K. Holland, J. van Zelst, G. den Heeten, M. Imhof-Tas, R. Mann, C. van Gils and N. Karssemeijer, "Consistency of breast density categories in serial screening mammograms: A comparison between automated and human assessment",
Breast,
2016;29:49-54.
T. Tan, A. Gubern-Mérida, C. Borelli, R. Manniesing, J. van Zelst, L. Wang, W. Zhang, B. Platel, R. Mann and N. Karssemeijer, "Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model",
Medical Physics,
2016;43(7):4074-4084.
B. Bejnordi, M. Balkenhol, G. Litjens, R. Holland, P. Bult, N. Karssemeijer and J. van der Laak, "Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images",
IEEE Transactions on Medical Imaging,
2016;35(9):2141-2150.
J. Mordang, A. Gubern-Mérida, G. den Heeten and N. Karssemeijer, "Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications",
Medical Physics,
2016;43(4):1676-1687.
M. Kallenberg, K. Petersen, M. Nielsen, A. Ng, P. Diao, C. Igel, C. Vachon, K. Holland, N. Karssemeijer and M. Lillholm, "Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring",
IEEE Transactions on Medical Imaging,
2016;35:1322-1331.
S. Schalekamp, N. Karssemeijer, A. Cats, B. De Hoop, B. Geurts, O. Berger-Hartog, B. van Ginneken and C. Schaefer-Prokop, "The Effect of Supplementary Bone-Suppressed Chest Radiographs on the Assessment of a Variety of Common Pulmonary Abnormalities: Results of an Observer Study",
Journal of Thoracic Imaging,
2016;31(2):119-125.
A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, S. Lardenoije, R. Mann, N. Karssemeijer and B. Platel, "Automated detection of breast cancer in false-negative screening MRI studies from women at increased risk",
European Journal of Radiology,
2016;85(2):472-479.
M. Dalmis, A. Gubern-Mérida, S. Vreemann, N. Karssemeijer, R. Mann and B. Platel, "A Computer-Aided Diagnosis System for Breast DCE-MRI at High Spatiotemporal Resolution",
Medical Physics,
2016;43(1):84-94.
B. Bejnordi, G. Litjens, N. Timofeeva, I. Otte-Holler, A. Homeyer, N. Karssemeijer and J. van der Laak, "Stain specific standardization of whole-slide histopathological images",
IEEE Transactions on Medical Imaging,
2016;35(2):404-415.
A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann and N. Karssemeijer, "Automated linking of suspicious findings between automated 3D breast ultrasound volumes",
Medical Imaging,
2016.
A. Bria, C. Marrocco, N. Karssemeijer, M. Molinara and F. Tortorella, "Deep Cascade Classifiers to Detect Clusters of Microcalcifications",
Breast Imaging,
2016;9699:415-422.
M. Kallenberg, M. Nielsen, K. Holland, N. Karssemeijer, C. Igel and M. Lillholm, "Learning Density Independent Texture Features",
Breast Imaging,
2016;9699:299-306.
A. Bria, C. Marrocco, J. Mordang, N. Karssemeijer, M. Molinara and F. Tortorella, "LUT-QNE: Look-Up-Table Quantum Noise Equalization in Digital Mammograms",
Breast Imaging,
2016;9699:27-34.
T. Mertzanidou, J. Hipwell, S. Reis, B. Bejnordi, M. Hermsen, M. Dalmis, S. Vreemann, B. Platel, J. van der Laak, N. Karssemeijer, R. Mann, P. Bult and D. Hawkes, "Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology",
Breast Imaging,
2016;9699:367-374.
K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "Quantification of mammographic masking risk with volumetric breast density maps: How to select women for supplemental screening",
Medical Imaging,
2016.
T. Kooi, A. Gubern-Mérida, J. Mordang, R. Mann, R. Pijnappel, K. Schuur, A. den Heeten and N. Karssemeijer, "A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography",
Breast Imaging,
2016;9699:51-56.
M. Ufuk Dalmiş, A. Gubern-Mérida, C. Borelli, S. Vreemann, R. Mann and N. Karssemeijer, "A fully automated system for quantification of background parenchymal enhancement in breast DCE-MRI",
Medical Imaging 2016: Computer-Aided Diagnosis,
2016.
J. Mordang, T. Janssen, A. Bria, T. Kooi, A. Gubern-Mérida and N. Karssemeijer, "Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks",
Breast Imaging,
2016;9699:35-42.
K. Holland, I. Sechopoulos, G. den Heeten, R. Mann and N. Karssemeijer, "Performance of breast cancer screening depends on mammographic compression",
Breast Imaging,
2016;9699:183-189.
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, F. de Leeuw, E. Marchiori, B. van Ginneken and B. Platel, "Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation",
IEEE International Symposium on Biomedical Imaging,
2016:1414-1417.
S. Vreemann, A. Gubern-Mérida, S. Lardenoije, N. Karssemeijer and R. Mann, "Prognostic factors of interval carcinomas occurring in an intermediate and high risk breast cancer screening program",
European Congress of Radiology,
2016.
N. Karssemeijer, K. Holland, I. Sechopoulos, R. Mann, G. den Heeten and C. van Gils, "High Breast Compression in Mammography May Reduce Sensitivity",
Annual Meeting of the Radiological Society of North America,
2016.
J. Wanders, K. Holland, P. Peeters, N. Karssemeijer and C. van Gils, "Volumetric Breast Density And The Risk Of Screen-Detected And Interval Breast Cancer",
Annual conference of the International Agency for Research on Cancer,
2016.
S. Vreemann, A. Gubern-Mérida, C. Borelli, N. Karssemeijer and R. Mann, "Background Parenchymal Enhancement as a predictor of breast cancer grade: a pilot study",
European Congress of Radiology,
2016.
S. Vreemann, A. Gubern-Mérida, S. Lardenoije, N. Karssemeijer and R. Mann, "Differences between cancers detected in prophylactic mastectomy specimen, screen detected cancers and true interval cancers in women participating in an intermediate and high risk screening program",
European Breast Cancer Conference,
2016.
S. Vreemann, A. Gubern-Mérida, S. Lardenoije, N. Karssemeijer and R. Mann, "The performance of MRI screening in the detection of breast cancer in an intermediate and high risk screening program",
Annual Meeting of the International Society for Magnetic Resonance in Medicine,
2016.
K. Kallenberg, M. Nielsen, K. Holland, N. Karssemeijer and M. Lillholm, "Breast Cancer Risk Prediction with Density Independent Texture Features",
Annual Meeting of the Radiological Society of North America,
2016.
M. Razavi, L. Wang, T. Tan, N. Karssemeijer, L. Linsen, U. Frese, H. Hahn and G. Zachmann, "Novel Morphological Features for Non-mass-like Breast Lesion Classification on DCE-MRI",
Machine Learning in Medical Imaging,
2016:305-312.
D. van der Waal, M. Emaus, M. Bakker, G. den Heeten, N. Karssemeijer, R. Pijnappel, W. Veldhuis, A. Verbeek, C. van Gils and M. Broeders, "Geographic variation in volumetric breast density between screening regions in the Netherlands",
European Radiology,
2015;25(11):3328-3337.
M. Emaus, M. Bakker, P. Peeters, C. Loo, R. Mann, M. de Jong, R. Bisschops, J. Veltman, K. Duvivier, M. Lobbes, R. Pijnappel, N. Karssemeijer, H. de Koning, M. van den Bosch, E. Monninkhof, W. Mali, W. Veldhuis and C. van Gils, "MR Imaging as an Additional Screening Modality for the Detection of Breast Cancer in Women Aged 50-75 Years with Extremely Dense Breasts: The DENSE Trial Study Design",
Radiology,
2015;277(2):527-537.
G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI",
European Radiology,
2015;25(11):3187-3199.
W. van de Ven, Y. Hu, J. Barentsz, N. Karssemeijer, D. Barratt and H. Huisman, "Biomechanical modeling constrained surface-based image registration for prostate MR guided TRUS biopsy",
Medical Physics,
2015;42:2470-2481.
T. Tan, J. Mordang, J. van Zelst, A. Grivegnée, A. Gubern-Mérida, J. Melendez, R. Mann, W. Zhang, B. Platel and N. Karssemeijer, "Computer-aided detection of breast cancers using Haar-like features in automated 3D breast ultrasound",
Medical Physics,
2015;42(7):1498-1504.
A. Bluekens, W. Veldkamp, K. Schuur, N. Karssemeijer, M. Broeders and G. den Heeten, "The potential use of ultra-low radiation dose images in digital mammography - a clinical proof-of-concept study in craniocaudal views",
British Journal of Radiology,
2015;88(1047):20140626.
A. Gubern-Mérida, M. Kallenberg, R. Mann, R. Marti and N. Karssemeijer, "Breast Segmentation and Density Estimation in Breast MRI: A Fully Automatic Framework",
IEEE Journal of Biomedical and Health Informatics,
2015;19(1):349-357.
A. Gubern-Mérida, R. Marti, J. Melendez, J. Hauth, R. Mann, N. Karssemeijer and B. Platel, "Automated localization of breast cancer in DCE-MRI",
Medical Image Analysis,
2015;20(1):265-274.
J. Van Zelst, B. Platel, N. Karssemeijer and R. Mann, "Multiplanar reconstructions of 3D automated breast ultrasound improve lesion differentiation by radiologists",
Academic Radiology,
2015;22(12):1489-1496.
A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann, B. Platel and N. Karssemeijer, "Pectoral muscle surface segmentation in automated 3D breast ultrasound using cylindrical transform and atlas information",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2015.
M. Ghafoorian, N. Karssemeijer, F. de Leeuw, T. Heskes, E. Marchiori and B. Platel, "Small White Matter Lesion Detection in Cerebral Small Vessel Disease",
Medical Imaging,
2015;9414:941411.
B. Bejnordi, G. Litjens, M. Hermsen, N. Karssemeijer and J. van der Laak, "A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images",
Medical Imaging,
2015;9420:94200H.
M. Kallenberg, M. Lillholm, P. Diao, K. Petersen, K. Holland, N. Karssemeijer, C. Igel and M. Nielsen, "Assessing Breast Cancer Masking Risk with Automated Texture Analysis in Full Field Digital Mammography",
Annual Meeting of the Radiological Society of North America,
2015.
A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, S. Lardenoije, R. Mann, B. Platel and N. Karssemeijer, "Automated detection of breast cancer as an aid in the interpretation of screening MRI",
European Congress of Radiology,
2015.
M. Dalmis, A. Gubern-Mérida, S. Vreemann, R. Mann, N. Karssemeijer and B. Platel, "Early Phase Contrast Enhancement Dynamics of Breast Lesions of Different Molecular Subtypes Characterized by a Computer-Aided-Diagnosis System",
Annual Meeting of the Radiological Society of North America,
2015.
J. Wanders, K. Holland, P. Peeters, N. Karssemeijer and C. van Gils, "Volumetric breast density and the risk of screen detected and interval breast cancer",
7th International Workshop on Breast Densitometry and Cancer Risk Assessment,
2015.
J. Wanders, K. Holland, P. Peeters, N. Karssemeijer and C. van Gils, "Combined effect of dense and nondense breast volume on breast cancer risk",
7th International Workshop on Breast Densitometry and Cancer Risk Assessment,
2015.
S. Vreemann, A. Gubern-Mérida, S. Lardenoije, B. Platel, N. Karssemeijer and R. Mann, "A critical audit of a breast MRI screening programme for intermediate and high risk patients in clinical practice",
European Congress of Radiology,
2015.
M. Kallenberg, K. Petersen, M. Lillholm, D. JAfA rgensen, P. Diao, K. Holland, N. Karssemeijer, C. Igel and M. Nielsen, "Automated texture scoring for assessing breast cancer masking risk in full field digital mammography",
European Congress of Radiology,
2015.
K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "Consistency of density categories over multiple screening rounds using volumetric breast density",
Annual Meeting of the Radiological Society of North America,
2015.
S. Vreemann, A. Gubern-Mérida, S. Lardenoije, B. Platel, N. Karssemeijer and R. Mann, "Breast cancers not detected by MRI in a high and intermediate risk screening program",
Annual Meeting of the Radiological Society of North America,
2015.
J. Wanders, K. Holland, W. Veldhuis, R. Mann, P. Peeters, C. van Gils and N. Karssemeijer, "Effect of volumetric mammographic density on performance of a breast cancer screening program using full-field digital mammography",
7th International Workshop on Breast Densitometry and Cancer Risk Assessment,
2015.
K. Holland, A. Gubern-Mérida, R. Mann and N. Karssemeijer, "Improved volumetric breast density assessment in dense breasts",
7th International Workshop on Breast Densitometry and Cancer Risk Assessment,
2015.
M. Dalmis, A. Gubern-Mérida, S. Vreemann, B. Platel, R. Mann and N. Karssemeijer, "Is Late Phase Information Necessary for Dynamic Evaluation of Breast Cancer?",
European Congress of Radiology,
2015.
K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "Optimisation of the selection of women with an increased risk of a masked tumour for supplementary screening",
Annual Meeting of the Radiological Society of North America,
2015.
A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann, B. Platel and N. Karssemeijer, "Evaluation of a Novel Method to Segment the Pectoral Muscle Surface in Automated Whole Breast Ultrasound",
Annual Meeting of the Radiological Society of North America,
2015.
J. Wanders, K. Holland, W. Veldhuis, R. Mann, P. Peeters, C. van Gils and N. Karssemeijer, "Effect of volumetric mammographic density on performance of a breast cancer screening program using full-field digital mammography",
European Congress of Radiology,
2015.
A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, R. Mann, B. Platel and N. Karssemeijer, "Automated Detection of Mass-like, Non-mass-like and Focus Breast Cancer Lesions Visible in False-negative Screening DCE-MRI",
Annual Meeting of the Radiological Society of North America,
2015.
K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "How can we identify women at risk for a masked cancer, who may benefit from supplemental screening?",
Annual Meeting of the Radiological Society of North America,
2015.
M. Kallenberg, M. Lillholm, P. Diao, K. Holland, N. Karssemeijer, C. Igel and M. Nielsen, "Assessing breast cancer masking risk in full field digital mammography with automated texture analysis",
7th International Workshop on Breast Densitometry and Cancer Risk Assessment,
2015.
S. Vreemann, A. Gubern-Mérida, S. Lardenoije, B. Platel, N. Karssemeijer and R. Mann, "Longitudinal results of a breast MRI screening program for patients at high and intermediate risk; does BRCA status matter?",
Annual Meeting of the Radiological Society of North America,
2015.
M. Razavi, L. Wang, A. Gubern-Mérida, T. Ivanovska, H. Laue, N. Karssemeijer and H. Hahn, "Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal",
Lecture Notes in Computer Science,
2015:528-536.
G. Karemore, M. Nielsen, N. Karssemeijer and S. Brandt, "A method to determine the mammographic regions that show early changes due to the development of breast cancer",
Physics in Medicine and Biology,
2014;59(22):6759-6773.
S. Schalekamp, B. van Ginneken, I. van den Berk, I. Hartmann, M. Snoeren, A. Odink, W. van Lankeren, S. Pegge, L. Schijf, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression increases the visibility of invasive pulmonary aspergillosis in chest radiographs",
PLoS One,
2014;9(10):e108551.
J. Melendez, C. Sánchez, B. van Ginneken and N. Karssemeijer, "Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection",
Medical Physics,
2014;41(8):081904.
G. Litjens, O. Debats, J. Barentsz, N. Karssemeijer and H. Huisman, "Computer-aided detection of prostate cancer in MRI",
IEEE Transactions on Medical Imaging,
2014;33(5):1083-1092.
R. Mann, R. Mus, J. van Zelst, C. Geppert, N. Karssemeijer and B. Platel, "A Novel Approach to Contrast-Enhanced Breast Magnetic Resonance Imaging for Screening: High-Resolution Ultrafast Dynamic Imaging",
Investigative Radiology,
2014;49(9):579-585.
S. Schalekamp, B. van Ginneken, E. Koedam, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone suppressed images",
Radiology,
2014;272(1):252-261.
S. Schalekamp, B. van Ginneken, E. Koedam, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer-aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone-suppressed images",
Radiology,
2014;272(1):252-261.
S. Schalekamp, B. van Ginneken, B. Heggelman, M. Imhof-Tas, I. Somers, M. Brink, M. Spee, C. Schaefer-Prokop and N. Karssemeijer, "New methods for using computer-aided detection information for the detection of lung nodules on chest radiographs",
British Journal of Radiology,
2014;87(1036):20140015.
J. Bozek, M. Kallenberg, M. Grgic and N. Karssemeijer, "Use of volumetric features for temporal comparison of mass lesions in full field digital mammograms",
Medical Physics,
2014;41(2):021902.
S. Schalekamp, B. van Ginneken, N. Karssemeijer and C. Schaefer-Prokop, "Chest radiography: new technological developments and their applications",
Seminars in Respiratory and Critical Care Medicine,
2014;35(1):3-16.
A. Gubern-Mérida, M. Kallenberg, B. Platel, R. Mann, R. Marti and N. Karssemeijer, "Volumetric breast density estimation from Full-Field Digital Mammograms: A validation study",
PLoS One,
2014;9(1):e85952.
B. Platel, R. Mus, T. Welte, N. Karssemeijer and R. Mann, "Automated Characterization of Breast Lesions Imaged with an Ultrafast DCE-MR Protocol",
IEEE Transactions on Medical Imaging,
2014:225-232.
S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, "Influence of study design in receiver operating characteristics studies: sequential versus independent reading",
Journal of Medical Imaging,
2014;1(1):015501-015501.
H. Liu, T. Tan, J. van Zelst, R. Mann, N. Karssemeijer and B. Platel, "Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound",
Journal of Medical Imaging,
2014;1(2):024501-024501.
J. Mordang, J. Hauth, G. den Heeten and N. Karssemeijer, "Automated Labeling of Screening Mammograms with Arterial Calcifications",
Breast Imaging,
2014;8539.
K. Holland, M. Kallenberg, R. Mann, C. van Gils and N. Karssemeijer, "Stability of Volumetric Tissue Composition Measured in Serial Screening Mammograms",
Breast Imaging -12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 AC/a,!aEURoe July 2, 2014. Proceedings,
2014;8539.
B. Ehteshami Bejnordi, N. Timofeeva, I. Otte-Höller, N. Karssemeijer and J. van der Laak, "Quantitative analysis of stain variability in histology slides and an algorithm for standardization",
Medical Imaging,
2014.
G. Litjens, N. Karssemeijer, J. Barentsz and H. Huisman, "Computer-aided Detection of Prostate Cancer in Multi-parametric Magnetic Resonance Imaging",
Annual Meeting of the Radiological Society of North America,
2014.
S. Schalekamp, N. Karssemeijer, C. Schaefer-Prokop and B. van Ginneken, "Double reading improves detection of small lung tumors in chest radiographs: can a computer aided detection system replace the second reader?",
European Congress of Radiology,
2014.
S. Schalekamp, I. van den Berk, I. Hartmann, M. Snoeren, A. Odink, S. Pegge, L. Schijf, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppressed images improve pulmonary fungal infection detection in chest radiographs",
European Congress of Radiology,
2014.
W. van de Ven, S. Rinsma, N. Karssemeijer, J. Barentsz and H. Huisman, "Electro-magnetic tracker-based fusion for image-guided TRUS prostate biopsy",
European Congress of Radiology,
2014.
A. Bria, N. Karssemeijer and F. Tortorella, "Learning from unbalanced data: A cascade-based approach for detecting clustered microcalcifications",
Medical Image Analysis,
2013;18(2):241-252.
T. Tan, B. Platel, T. Twellmann, G. van Schie, R. Mus, A. Grivegnée, R. Mann and N. Karssemeijer, "Evaluation of the Effect of Computer-Aided Classification of Benign and Malignant Lesions on Reader Performance in Automated Three-dimensional Breast Ultrasound",
Academic Radiology,
2013;20(11):1381-1388.
S. Schalekamp, B. van Ginneken, L. Meiss, L. Peters-Bax, L. Quekel, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs",
European Journal of Radiology,
2013;82(12):2399-2405.
G. van Schie, R. Mann, M. Imhof-Tas and N. Karssemeijer, "Generating synthetic mammograms from reconstructed tomosynthesis volumes",
IEEE Transactions on Medical Imaging,
2013;32(12):2322-2331.
T. Tan, B. Platel, R. Mus, L. Tabar, R. Mann and N. Karssemeijer, "Computer-aided Detection of Cancer in Automated 3D Breast Ultrasound",
IEEE Transactions on Medical Imaging,
2013;32:1698-1706.
M. Giger, N. Karssemeijer and J. Schnabel, "Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer",
Annual Review of Biomedical Engineering,
2013;15:327-57.
G. van Schie, M. Wallis, K. Leifland, M. Danielsson and N. Karssemeijer, "Mass detection in reconstructed digital breast tomosynthesis volumes with a computer-aided detection system trained on 2D mammograms",
Medical Physics,
2013;40(4):041902.
M. Velikova, P. Lucas, M. Samulski and N. Karssemeijer, "On the interplay of machine learning and background knowledge in image interpretation by Bayesian Networks",
Artificial Intelligence in Medicine,
2013;57:73AC/a,!aEURoe86.
T. Tan, B. Platel, R. Mann, H. Huisman and N. Karssemeijer, "Chest Wall Segmentation in Automated 3D Breast Ultrasound Scans",
Medical Image Analysis,
2013;17:1273AC/a,!aEURoe1281.
R. Hupse, M. Samulski, M. Lobbes, R. Mann, R. Mus, G. den Heeten, D. Beijerinck, R. Pijnappel, C. Boetes and N. Karssemeijer, "Computer-aided Detection of Masses at Mammography: Interactive Decision Support versus Prompts",
Radiology,
2013;266:123-129.
R. Hupse, M. Samulski, M. Lobbes, A. den Heeten, M. Imhof-Tas, D. Beijerinck, R. Pijnappel, C. Boetes and N. Karssemeijer, "Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses",
European Radiology,
2013;23:93-100.
T. Tan, B. Eiben, B. Platel, J. Zelst, L. Han, T. Mertzanidou, S. Johnsen, J. Hipwell, R. Mann, D. Hawkes and N. Karssemeijer, "Registration of automated 3D breast ultrasound views",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2013.
A. Gubern-Mérida, L. Wang, M. Kallenberg, R. Martí, H. Hahn and N. Karssemeijer, "Breast segmentation in MRI: quantitative evaluation of three methods",
Medical Imaging,
2013:86693G-86693G-7.
S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, "Impact of Bone Suppression Imaging on the Detection of Lung Nodules in Chest Radiographs: Analysis of Multiple Reading Sessions",
Medical Imaging,
2013:86730Y.
W. van de Ven, Y. Hu, J. Barentsz, N. Karssemeijer, D. Barratt and H. Huisman, "Surface-based prostate registration with biomechanical regularization",
Medical Imaging,
2013;8671:86711R.
A. Gubern-Mérida, B. Platel, R. Martí and N. Karssemeijer, "Automated localization of malignant lesions in breast DCE-MRI",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2013.
S. Schalekamp, B. van Ginneken, M. Brink, B. Heggelman, M. Spee, I. Somers, N. Karssemeijer and C. Schaefer-Prokop, ""Computer Aided Detection shows added value to Bone Suppression Imaging for the detection of lung nodules in chest radiographs"",
WCTI,
2013.
S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, ""Computer aided detection of lung nodules in chest radiographs: novel approaches to improve reader performance"",
MIPS,
2013.
G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Initial prospective evaluation of the prostate imaging reporting and data standard (PI-RADS): Can it reduce unnecessary MR guided biopsies?",
Annual Meeting of the Radiological Society of North America,
2013.
J. van Zelst, R. Mus, T. Tan, N. Karssemeijer and R. Mann, "Feasibility of automated 3D breast ultrasound scanning in screening of women with high risk",
European Congress of Radiology,
2013.
J. van Zelst, T. Tan, B. Platel, N. Karssemeijer and R. Mann, "Evaluation of spiculation and retraction patterns in coronal reconstructions in 3D Automated Breast Ultrasound (ABUS) improve differentiation between benign and malignant breast lesions",
Annual Meeting of the Radiological Society of North America,
2013.
W. van de Ven, N. Karssemeijer, J. Barentsz and H. Huisman, "Image registration for prostate MR guided biopsy using automated biomechanical modeling",
Annual Meeting of the Radiological Society of North America,
2013.
S. Schalekamp, N. Karssemeijer, C. Schaefer-Prokop and B. van Ginneken, ""Independent combination of multiple readers for the detection of lung nodules in chest radiographs: setting a benchmark for computer-aided detection"",
Annual Meeting of the Radiological Society of North America,
2013.
A. Bluekens, R. Holland, N. Karssemeijer, M. Broeders and G. den Heeten, "Comparison of Digital Screening Mammography and Screen-Film Mammography in the Early Detection of Clinically Relevant Cancers: A Multicenter Study",
Radiology,
2012;265:707-714.
J. Lesniak, R. Hupse, R. Blanc, N. Karssemeijer and G. Székely, "Comparative evaluation of support vector machine classification for computer aided detection of breast masses in mammography",
Physics in Medicine and Biology,
2012;57(16):5295-5307.
M. Kallenberg, C. van Gils, M. Lokate, G. den Heeten and N. Karssemeijer, "Effect of compression paddle tilt correction on volumetric breast density estimation",
Physics in Medicine and Biology,
2012;57(16):5155-5168.
M. Stoutjesdijk, M. Zijp, C. Boetes, N. Karssemeijer, J. Barentsz and H. Huisman, "Computer aided analysis of breast MRI enhancement kinetics using mean shift c lustering and multifeature iterative region of interest selection",
Journal of Magnetic Resonance Imaging,
2012;36:1104-1112.
T. Mertzanidou, J. Hipwell, M. Cardoso, X. Zhang, C. Tanner, S. Ourselin, U. Bick, H. Huisman, N. Karssemeijer and D. Hawkes, "MRI to X-ray mammography registration using a volume-preserving affine transformation",
Medical Image Analysis,
2012;16(5):966-975.
P. Vos, J. Barentsz, N. Karssemeijer and H. Huisman, "Automatic computer-aided detection of prostate cancer based on multiparametric magnetic resonance image analysis",
Physics in Medicine and Biology,
2012;57(6):1527-1542.
M. Velikova, P. Lucas, M. Samulski and N. Karssemeijer, "A probabilistic framework for image information fusion with an application to mammographic analysis",
Medical Image Analysis,
2012;16:865-875.
T. Tan, B. Platel, H. Huisman, C. Sánchez, R. Mus and N. Karssemeijer, "Computer Aided Lesion Diagnosis in Automated 3D Breast Ultrasound Using Coronal Spiculation",
IEEE Transactions on Medical Imaging,
2012;31(5):1034-1042.
M. Kallenberg and N. Karssemeijer, "Compression paddle tilt correction in full-field digital mammograms",
Physics in Medicine and Biology,
2012;57(3):703-715.
R. Visser, W. Veldkamp, D. Beijerinck, P. Bun, J. Deurenberg, M. Imhof-Tas, K. Schuur, M. Snoeren, G. den Heeten, N. Karssemeijer and M. Broeders, "Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography",
European Radiology,
2012;22(4):908-914.
A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer, "Segmentation of the pectoral muscle in breast MRI using atlas-based approaches",
Medical Image Computing and Computer-Assisted Intervention,
2012;15(Pt 2):371-378.
G. Litjens, O. Debats, W. van de Ven, N. Karssemeijer and H. Huisman, "A pattern recognition approach to zonal segmentation of the prostate on MRI",
Medical Image Computing and Computer-Assisted Intervention,
2012;7511:413-420.
J. Lesniak, G. van Schie, C. Tanner, B. Platel, H. Huisman, N. Karssemeijer and G. Szekely, "Multimodal Classification of Breast Masses in Mammography and MRI using Unimodal Feature Selection and Decision Fusion",
IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging,
2012;7361:88-95.
J. Bozek, M. Kallenberg, M. Grgic and N. Karssemeijer, "Comparison of Lesion Size Using Area and Volume in Full Field Digital Mammograms",
IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging,
2012;7361:96-103.
J. Melendez, C. Sánchez, R. Hupse, B. van Ginneken and N. Karssemeijer, "Potential of a Standalone Computer-Aided Detection System for Breast Cancer Detection in Screening Mammography",
IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging,
2012;7361:682-689.
T. Tan, B. Platel, R. Mus and N. Karssemeijer, "Detection of Breast Cancer in Automated 3D Breast Ultrasound",
Medical Imaging,
2012;8315:831505-1-831505-8.
C. Tromans, G. van Schie, N. Karssemeijer and M. Brady, "A Hypothesis-Test Framework for Quantitative Lesion Detection and Diagnosis",
IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging,
2012;7361:458-465.
G. Litjens, N. Karssemeijer and H. Huisman, "A multi-atlas approach for prostate segmentation in MRI",
MICCAI} {W}orkshop: {P}rostate {C}ancer {I}maging: The {PROMISE12} Prostate Segmentation Challenge,
2012.
G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach",
Medical Imaging,
2012;8315(1):83150G-83150G-6.
J. Melendez, C. Sánchez, B. van Ginneken and N. Karssemeijer, "Detection of breast carcinomas potentially missed during screening by means of a standalone CAD system",
Annual Meeting of the Radiological Society of North America,
2012.
R. Mus, R. Mann, A. Moyakine, C. Geppert, B. Platel, N. Karssemeijer and J. Barentsz, "MRI Screening of the Breast in Less than 2 Minutes: A Prelude to Extend MR Breast Screening Possibilities",
Annual Meeting of the Radiological Society of North America,
2012.
S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, L. Meiss, A. Tiehuis, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression imaging improves observer performance for the detection of lung nodules in chest radiographs",
Annual Meeting of the Radiological Society of North America,
2012.
G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Computerized characterization of central gland lesions using texture and relaxation features from T2-weighted prostate MRI",
Annual Meeting of the Radiological Society of North America,
2012.
M. Kallenberg, C. van Gils, R. Mann and N. Karssemeijer, "Association between automated, volumetric measures of breast density and diagnostic outcome of mammography screening examinations",
Annual Meeting of the Radiological Society of North America,
2012.
S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, L. Meiss, A. Tiehuis, E. Koedam, L. Quekel, M. Snoeren, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Botsuppressie in thoraxfoto's verbetert de detectie van pulmonale nodules door radiologen",
Radiologen Dagen,
2012.
R. Mann, R. Mus, C. Geppert, C. Frentz, N. Karssemeijer, H. Huisman and B. Platel, "Initial maximum slope of the contrast enhancement versus time curve for dynamic evaluation of breast lesions on ultrafast breast MRIs",
European Congress of Radiology,
2012.
B. Platel, T. Welte, R. Mus, R. Mann, C. Sánchez, H. Hahn and N. Karssemeijer, "Automated Evaluation of an Ultrafast MR Imaging Protocol for the Characterization of Breast Lesions",
Annual Meeting of the Radiological Society of North America,
2012.
S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, M. Snoeren, L. Quekel, E. Koedam, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression imaging improves observer performance for the detection of lung nodules in chest radiographs",
Annual Meeting of the European Society of Thoracic Imaging,
2012.
S. Schalekamp, B. van Ginneken, E. Koedam, L. Quekel, M. Snoeren, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer aided detection helps radiologists to detect pulmonary nodules in chest radiographs, when having bone suppressed images available",
Annual Meeting of the Radiological Society of North America,
2012.
R. Mann, R. Mus, C. Geppert, C. Frentz, N. Karssemeijer, H. Huisman and B. Platel, "Dynamic analysis of breast lesions: Can we use the wash-in phase instead of the wash-out phase?",
Annual Meeting of the International Society for Magnetic Resonance in Medicine,
2012.
O. Debats, G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Automated 3-Dimensional Segmentation of Pelvic Lymph Nodes in Magnetic Resonance Images",
Medical Physics,
2011;38(11):6178-6187.
J. van Dijck, J. Otten, N. Karssemeijer, P. Kenemans, A. Verbeek and M. van der Mooren, "Less mammographic density after nasal versus oral administration of postmenopausal hormone therapy",
Climacteric,
2011;14(6):683-688.
G. van Schie, C. Tanner, P. Snoeren, M. Samulski, K. Leifland, M. Wallis and N. Karssemeijer, "Correlating locations in ipsilateral breast tomosynthesis views using an analytical hemispherical compression model",
Physics in Medicine and Biology,
2011;56(15):4715-4730.
S. Brandt, G. Karemore, N. Karssemeijer and M. Nielsen, "An Anatomically Oriented Breast Coordinate System for Mammogram Analysis",
IEEE Transactions on Medical Imaging,
2011;30(10):1841-1851.
M. Kallenberg, M. Lokate, C. van Gils and N. Karssemeijer, "Automatic breast density segmentation: an integration of different approaches",
Physics in Medicine and Biology,
2011;56(9):2715-2729.
M. Samulski and N. Karssemeijer, "Optimizing Case-based Detection Performance in a Multiview CAD System for Mammography",
IEEE Transactions on Medical Imaging,
2011;30(4):1001-1009.
M. Nielsen, G. Karemore, M. Loog, J. Raundahl, N. Karssemeijer, J. Otten, M. Karsdal, C. Vachon and C. Christiansen, "A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer",
Cancer Epidemiology,
2011;35(4):381-387.
G. van Schie, C. Tanner and N. Karssemeijer, "Estimating corresponding locations in ipsilateral breast tomosynthesis views",
Medical Imaging,
2011;7963:796306.
T. Tan, B. Platel, H. Huisman and N. Karssemeijer, "Chest wall segmentation in automated 3D breast ultrasound using a cylinder model",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2011.
A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer, "Fully automatic fibroglandular tissue segmentation in breast MRI: atlas-based approach",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2011.
T. Tan, B. Platel, T. Twellmann, G. van Schie, R. Mus, A. Grivegnee, L. Tabar and N. Karssemeijer, "Computer aided interpretation of lesions in automated 3D breast ultrasound",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2011.
M. Samulski, P. Snoeren, B. Platel, B. van Ginneken, L. Hogeweg, C. Schaefer-Prokop and N. Karssemeijer, "Computer-Aided Detection as a Decision Assistant in Chest Radiography",
Medical Imaging,
2011;7966(1):796614-1-796614-6.
T. Tan, H. Huisman, B. Platel, A. Grivignee, R. Mus and N. Karssemeijer, "Classification of Breast Lesions in Automated 3D Breast Ultrasound",
Medical Imaging,
2011;7963:79630X.
C. Tanner, G. van Schie, N. Karssemeijer and G. Szekely, "Matching Regions for Mammographic Views: Comparison and Compensation for Deformations",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2011.
P. Maduskar, L. Hogeweg, H. Ayles, R. Dawson, P. de Jong, N. Karssemeijer and B. van Ginneken, "Cavity segmentation in chest radiographs",
The Fourth International Workshop on Pulmonary Image Analysis,
2011.
J. Lesniak, R. Hupse, M. Kallenberg, M. Samulski, R. Blanc, N. Karssemeijer and G. Székely, "Computer Aided Detection of Breast Masses in Mammography using Support Vector Machine Classification",
Medical Imaging,
2011;7963(1):79631K.
G. Litjens, P. Vos, J. Barentsz, N. Karssemeijer and H. Huisman, "Automatic Computer Aided Detection of Abnormalities in Multi-Parametric Prostate MRI",
Medical Imaging,
2011;7963(1).
M. Kallenberg, M. Lokate, C. van Gils and N. Karssemeijer, "Automatic breast density segmentation based on pixel classification",
Medical Imaging,
2011;7963(1):796307.
B. Platel, H. Huisman, H. Laue, R. Mus, R. Mann, H. Hahn and N. Karssemeijer, "Computerized Characterization of Breast Lesions using Dual-Temporal Resolution Dynamic Contrast-Enhanced MR Images",
MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis,
2011.
A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer, "Multi-class probabilistic atlas-based segmentation method in breast MRI",
Pattern Recognition and Image Analysis: proceedings of 5th Iberian Conference,
2011;5.
G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Zone-specific Automatic Computer-aided Detection of Prostate Cancer in MRI",
Annual Meeting of the Radiological Society of North America,
2011.
B. Schroeder, R. Highnam, A. Cave, J. Walker, N. Karssemeijer, M. Yaffe, R. Jong and O. Alonzo-Proulx, "At What Age Should Breast Screening Begin?",
Annual Meeting of the Radiological Society of North America,
2011.
N. Karssemeijer, T. Tan, B. Platel, T. Twellmann, L. Tabar, A. Grivignee, R. Mus and H. Huisman, "A Novel System for Computer-aided Lesion Classification in Automated 3D Breast Ultrasound",
Annual Meeting of the Radiological Society of North America,
2011.
B. Platel, H. Huisman, H. Laue, R. Mann, H. Hahn, N. Karssemeijer and R. Mus, "Computerized Characterization of Breast Masses Using Dual-Temporal Resolution Dynamic Contrast-enhanced MR Images",
Annual Meeting of the Radiological Society of North America,
2011.
G. Karemore, S. Brandt, N. Karssemeijer and M. Nielsen, "Discovery of Mammogram Regions That Show Early Changes Due to the Development of Breast Cancer: A Preliminary Work",
Annual Meeting of the Radiological Society of North America,
2011.
N. Karssemeijer, R. Hupse, M. Samulski, D. Beijerinck, G. Heeten and C. Boetes, "Concurrent Interactive Use of CAD for Detection of Masses in Mammograms",
Annual Meeting of the Radiological Society of North America,
2011.
N. Karssemeijer, T. Tan, T. Twellmann, G. van Schie, A. Grivignee, L. Tabar, R. Mann and R. Mus, "Computer Aided Interpretation of Lesions in Automated 3D Breast Ultrasound",
Annual Meeting of the Radiological Society of North America,
2011.
M. Lokate, M. Kallenberg, N. Karssemeijer, M. van den Bosch, P. Peeters and C. van Gils, "Volumetric breast density from full-field digital mammograms and its association with breast cancer risk factors: a comparison with a threshold method",
Cancer Epidemiology Biomarkers and Prevention,
2010;19(12):3096-3105.
M. Samulski, R. Hupse, C. Boetes, R. Mus, G. den Heeten and N. Karssemeijer, "Using Computer Aided Detection in Mammography as a Decision Support",
European Radiology,
2010;20(10):2323-2330.
R. Hupse and N. Karssemeijer, "The effect of feature selection methods on computer-aided detection of masses in mammograms",
Physics in Medicine and Biology,
2010;55(10):2893-2904.
A. Bluekens, N. Karssemeijer, D. Beijerinck, J. Deurenberg, R. van Engen, M. Broeders and G. den Heeten, "Consequences of digital mammography in population-based breast cancer screening: initial changes and long-term impact on referral rates",
European Radiology,
2010;20(9):2067-2073.
S. Timp, C. Varela and N. Karssemeijer, "Computer-aided diagnosis with temporal analysis to improve radiologists' interpretation of mammographic mass lesions",
IEEE Transactions on Information Technology in Biomedicine,
2010;14(3):803-808.
M. Velikova, P. Lucas and N. Karssemeijer, "Using local context information to improve automatic mammographic mass detection",
Studies in Health Technology and Informatics,
2010;160:1291-1295.
A. Makarau, H. Huisman, R. Mus, M. Zijp and N. Karssemeijer, "Breast MRI intensity non-uniformity correction using mean-shift",
Medical Imaging,
2010;7624:76242D.
P. Snoeren, G. Litjens, B. van Ginneken and N. Karssemeijer, "Training a Computer Aided Detection System with Simulated Lung Nodules in Chest Radiographs",
The Third International Workshop on Pulmonary Image Analysis,
2010:139-149.
M. Kallenberg and N. Karssemeijer, "Comparison of Tilt Correction Methods in Full Field Digital Mammograms",
IWDM '10: Proceedings of the 10th international workshop on Digital Mammography,
2010:191-196.
G. van Schie, M. K. Leifland, E. Moa, M. Hemmendorff and N. Karssemeijer, "The Effect of Slab Size on Mass Detection Performance of a Screen-Film CAD System in Reconstructed Tomosynthesis Volumes",
IWDM '10: Proceedings of the 10th international workshop on Digital Mammography,
2010:497-504.
O. Debats, N. Karssemeijer, J. Barentsz and H. Huisman, "Automated classification of lymph nodes in USPIO-enhanced MR-images: a comparison of three segmentation methods",
Medical Imaging,
2010;7624:76240Q.
H. Huisman, J. Veltman, M. Zijp, R. Mann, R. Mus and N. Karssemeijer, "Dual-Time Resolution Characterization of Masses on Breast DCEMR",
Annual Meeting of the Radiological Society of North America,
2010.
P. Vos, J. Fütterer, N. Karssemeijer and J. Huisman, "Computer-assisted Diagnosis of Prostate Cancer with Multimodal3T MR Imaging",
Annual Meeting of the Radiological Society of North America,
2010.
N. Karssemeijer, A. Bluekens, D. Beijerinck, J. Deurenberg, M. Beekman, R. Visser, R. van Engen, A. Bartels-Kortland and M. Broeders, "Breast cancer screening results 5 years after introduction of digital mammography in a population-based screening program",
Radiology,
2009;253(2):353-358.
R. Hupse and N. Karssemeijer, "Use of normal tissue context in computer-aided detection of masses in mammograms",
IEEE Transactions on Medical Imaging,
2009;28(12):2033-2041.
J. Iglesias and N. Karssemeijer, "Robust initial detection of landmarks in film-screen mammograms using multiple FFDM atlases",
IEEE Transactions on Medical Imaging,
2009;28(11):1815-1824.
M. Velikova, M. Samulski, P. Lucas and N. Karssemeijer, "Improved mammographic CAD performance using multi-view information: a Bayesian network framework",
Physics in Medicine and Biology,
2009;54(5):1131-1147.
R. Hupse and N. Karssemeijer, "The use of contextual information for computer aided detection of masses in mammograms",
Medical Imaging,
2009;7260:72600Q.
G. van Schie and N. Karssemeijer, "Noise model for microcalcification detection in reconstructed tomosynthesis slices",
Medical Imaging,
2009;7260:72600M.
M. Velikova, M. Samulski, P. Lucas and N. Karssemeijer, "Causal Probabilistic Modelling for Two-View Mammographic Analysis",
AIME '09: Proceedings of the 12th Conference on Artificial Intelligence in Medicine,
2009:395-404.
M. Kallenberg and N. Karssemeijer, "Using Volumetric Density Estimation in Computer Aided Mass Detection in Mammography",
Proceedings of SPIE – Volume 7263, Medical Imaging 2009: Computer-Aided Diagnosis,
2009;7263(1):72600T.
M. Samulski, A. Hupse, C. Boetes, G. den Heeten and N. Karssemeijer, "Analysis of probed regions in an interactive CAD system for the detection of masses in mammograms",
Medical Imaging,
2009;7263(1):726314.
M. Kallenberg and N. Karssemeijer, "Computer-aided detection of masses in full-field digital mammography using screen-film mammograms for training",
Physics in Medicine and Biology,
2008;53(23):6879-6891.
A. Eilertsen, N. Karssemeijer, P. Skaane, E. Qvigstad and P. Sandset, "Differential impact of conventional and low-dose oral hormone therapy, tibolone and raloxifene on mammographic breast density, assessed by an automated quantitative method",
British Journal of Obstetrics and Gynaecology,
2008;115(6):773-779.
N. Karssemeijer, M. Samulski, M. Kallenberg, A. Hupse, C. Boetes and G. den Heeten, "Effectiveness of an Interactive CAD System for Mammographic Mass Detection",
94th Radiological Society of North America Scientific Assembly and Annual Meeting,
2008.
M. Samulski, N. Karssemeijer, C. Boetes and G. den Heeten, "An Interactive Computer-aided Detection Workstation for Reading Mammograms",
94th Radiological Society of North America Scientific Assembly and Annual Meeting,
2008.
M. Velikova, M. Samulski, N. Karssemeijer and P. Lucas, "Toward Expert Knowledge Representation for Automatic Breast Cancer Detection",
AIMSA '08: Proceedings of the 13th international conference on Artificial Intelligence,
2008:333-344.
M. Kallenberg and N. Karssemeijer, "The Effect of Training with SFM Images in a FFDM CAD System",
Proceedings of SPIE – Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis,
2008;6915(1):691510.
N. Karssemeijer, A. Hupse, M. Samulski, M. Kallenberg, C. Boetes and G. Heeten, "An Interactive Computer Aided Decision Support System for Detection of Masses in Mammograms",
IWDM '08: Proceedings of the 9th international workshop on Digital Mammography,
2008:273-278.
G. van Schie and N. Karssemeijer, "Detection of Microcalcifications Using a Nonuniform Noise Model",
IWDM '08: Proceedings of the 9th international workshop on Digital Mammography,
2008:378-384.
M. Velikova, P. Lucas, N. Ferreira, M. Samulski and N. Karssemeijer, "A decision support system for breast cancer detection in screening programs",
Proceeding of the 2008 conference on ECAI 2008,
2008:658-662.
N. Karssemeijer, M. Samulski, G. den Heeten and C. Boetes, "Analysis of Observer Performance Based on Probing Patterns in an Interactive CAD System for Mammographic Mass Detection",
94th Radiological Society of North America Scientific Assembly and Annual Meeting,
2008.
M. Samulski and N. Karssemeijer, "Linking mass regions in mediolateral oblique and cranio caudal views",
Proceedings of the 14th ASCI conference,
2008:214-221.
M. Kallenberg and N. Karssemeijer, "The Effect of Training Sample Size on Performance of Mass Detection",
IWDM '08: Proceedings of the 9th international workshop on Digital Mammography,
2008:343-349.
M. Samulski and N. Karssemeijer, "Matching mammographic regions in mediolateral oblique and cranio caudal views: a probabilistic approach",
Medical Imaging,
2008;6915(1):69151M.
R. Hupse and N. Karssemeijer, "Feature selection for computer-aided detection: comparing different selection criteria",
Medical Imaging,
2008;6915:691503.
M. Stoutjesdijk, J. Veltman, H. Huisman, N. Karssemeijer, J. Barentsz, J. Blickman and C. Boetes, "Automated analysis of contrast enhancement in breast MRI lesions using mean shift clustering for ROI selection",
Journal of Magnetic Resonance Imaging,
2007;26(3):606-614.
S. Timp, C. Varela and N. Karssemeijer, "Temporal change analysis for characterization of mass lesions in mammography",
IEEE Transactions on Medical Imaging,
2007;26(7):945-953.
J. van Dalen, A. Hoffmann, V. Dicken, W. Vogel, B. Wiering, T. Ruers, N. Karssemeijer and W. Oyen, "A novel iterative method for lesion delineation and volumetric quantification with FDG PET",
Nuclear Medicine Communications,
2007;28(6):485-493.
S. van Engeland and N. Karssemeijer, "Combining two mammographic projections in a computer aided mass detection method",
Medical Physics,
2007;34(3):898-905.
P. Snoeren and N. Karssemeijer, "Gray-scale and geometric registration of full-field digital and film-screen mammograms",
Medical Image Analysis,
2007;11(2):146-156.
A. Roelofs, N. Karssemeijer, N. Wedekind, C. Beck, S. van Woudenberg, P. Snoeren, J. Hendriks, M. del Turco, N. Bjurstam, H. Junkermann, D. Beijerinck, B. Séradour and C. Evertsz, "Importance of comparison of current and prior mammograms in breast cancer screening",
Radiology,
2007;242(1):70-77.
H. Huisman and N. Karssemeijer, "Chestwall segmentation in 3D breast ultrasound using a deformable volume model",
Information Processing in Medical Imaging,
2007:245-256.
M. Samulski, N. Karssemeijer, P. Lucas and P. Groot, "Classification of mammographic masses using support vector machines and Bayesian networks",
Medical Imaging,
2007;6514(1):65141J.
N. Karssemeijer, J. Otten, H. Rijken and R. Holland, "Computer aided detection of masses in mammograms as decision support",
British Journal of Radiology,
2006;79 Spec No 2:S123-S126.
S. Selvan, C. Xavier, N. Karssemeijer, J. Sequeira, R. Cherian and B. Dhala, "Parameter estimation in stochastic mammogram model by heuristic optimization techniques",
IEEE Transactions on Information Technology in Biomedicine,
2006;10(4):685-695.
S. van Engeland, S. Timp and N. Karssemeijer, "Finding corresponding regions of interest in mediolateral oblique and craniocaudal mammographic views",
Medical Physics,
2006;33(9):3203-3212.
S. van Engeland, P. Snoeren, H. Huisman, C. Boetes and N. Karssemeijer, "Volumetric breast density estimation from full-field digital mammograms",
IEEE Transactions on Medical Imaging,
2006;25(3):273-282.
C. Varela, S. Timp and N. Karssemeijer, "Use of border information in the classification of mammographic masses",
Physics in Medicine and Biology,
2006;51(2):425-441.
A. Roelofs, S. van Woudenberg, J. Otten, J. Hendriks, A. Bödicker, C. Evertsz and N. Karssemeijer, "Effect of soft-copy display supported by CAD on mammography screening performance",
European Radiology,
2006;16(1):45-52.
S. Timp, S. van Engeland and N. Karssemeijer, "A regional registration method to find corresponding mass lesions in temporal mammogram pairs",
Medical Physics,
2005;32(8):2629-2638.
J. Otten, N. Karssemeijer, J. Hendriks, J. Groenewoud, J. Fracheboud, A. Verbeek, H. de Koning and R. Holland, "Effect of recall rate on earlier screen detection of breast cancers based on the Dutch performance indicators",
Journal of the National Cancer Institute,
2005;97(10):748-754.
C. Varela, N. Karssemeijer, J. Hendriks and R. Holland, "Use of prior mammograms in the classification of benign and malignant masses",
European Journal of Radiology,
2005;56(2):248-255.
W. Vogel, J. van Dalen, H. Huisman, W. Oyen and N. Karssemeijer, "Sliced alternating DICOM series: convenient visualisation of image fusion on PACS",
European Journal of Nuclear Medicine and Molecular Imaging,
2005;32(2):247-248.
N. Karssemeijer, P. Snoeren and W. Zhang, "Linearization of mammograms using parameters derived from noise characteristics",
Information Processing in Medical Imaging,
2005;3565:258-269.
S. van Engeland, C. Varela, S. Timp, P. Snoeren and N. Karssemeijer, "Using context for mass detection and classification in mammograms",
Medical Imaging,
2005;5794:94-102.
P. Snoeren and N. Karssemeijer, "Thickness correction of mammographic images by anisotropic filtering and interpolation of dense tissue",
Medical Imaging,
2005;5747:1521-1527.
S. van Engeland and N. Karssemeijer, "Regrouping initial CAD mass detections to facilitate classification of suspicious regions in mammography",
Medical Imaging,
2005;5747:975-986.
J. van Dalen, W. Vogel, H. Huisman, W. Oyen, G. Jager and N. Karssemeijer, "Accuracy of rigid CT-FDG-PET image registration of the liver",
Physics in Medicine and Biology,
2004;49(23):5393-5405.
P. Snoeren and N. Karssemeijer, "Thickness correction of mammographic images by means of a global parameter model of the compressed breast",
IEEE Transactions on Medical Imaging,
2004;23(7):799-806.
S. Timp and N. Karssemeijer, "A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography",
Medical Physics,
2004;31(5):958-971.
K. McLoughlin, P. Bones and N. Karssemeijer, "Noise equalization for detection of microcalcification clusters in direct digital mammogram images",
IEEE Transactions on Medical Imaging,
2004;23(3):313-320.
A. Roelofs, S. van Woudenberg, J. Hendriks, C. Evertsz and N. Karssemeijer, "Effects of computer-aided diagnosis on radiologists' detection of breast masses",
Digital Mammography,
2004:219-224.
N. Karssemeijer, J. Otten, A. Roelofs, S. van Woudenberg and J. Hendriks, "Effect of independent multiple reading of mammograms on detection performance",
Medical Imaging,
2004;5372:82-89.
S. van Engeland, P. Snoeren, J. Hendriks and N. Karssemeijer, "A comparison of methods for mammogram registration",
IEEE Transactions on Medical Imaging,
2003;22(11):1436-1444.
N. Karssemeijer, J. Otten, A. Verbeek, J. Groenewoud, H. de Koning, J. Hendriks and R. Holland, "Computer-aided detection versus independent double reading of masses on mammograms",
Radiology,
2003;227(1):192-200.
P. Snoeren and N. Karssemeijer, "Gray scale registration of mammograms using a model of image acquisition",
Information Processing in Medical Imaging,
2003;18:401-412.
T. Roelofs, S. van Woudenberg, J. Hendriks and N. Karssemeijer, "Optimized soft-copy display of digitized mammograms",
Medical Imaging,
2003;5034:10-19.
S. van Engeland, P. Snoeren, N. Karssemeijer and J. Hendriks, "Optimized perception of lesion growth in mammograms using digital display",
Medical Imaging,
2003;5034:25-31.
C. Varela, J. Muller and N. Karssemeijer, "Mammographic mass characterization using sharpness and lobulation measures",
Medical Imaging,
2003;5032:120-129.
S. Timp, N. Karssemeijer and J. Hendriks, "Analysis of changes in masses using contrast and size measures",
IWDM '02: Proceedings of the 6th international workshop on Digital Mammography,
2002:240-242.
S. van Engeland and N. Karssemeijer, "Matching breast lesions in multiple mammographic views",
Medical Image Computing and Computer-Assisted Intervention,
2001;2208/2010:1172-1173.
W. Veldkamp, N. Karssemeijer, J. Otten and J. Hendriks, "Automated classification of clustered microcalcifications into malignant and benign types",
Medical Physics,
2000;27(11):2600-2608.
G. te Brake, N. Karssemeijer and J. Hendriks, "An automatic method to discriminate malignant masses from normal tissue in digital mammograms",
Physics in Medicine and Biology,
2000;45(10):2843-2857.
C. van Gils, J. Hendriks, R. Holland, N. Karssemeijer, J. Otten, H. Straatman and A. Verbeek, "Changes in mammographic breast density and concomitant changes in breast cancer risk",
European Journal of Cancer Prevention,
1999;8(6):509-515.
N. Karssemeijer, W. Veldkamp, G. te Brake and J. Hendriks, "[Reading screening mammograms with the help of neural networks]",
Nederlands Tijdschrift voor Geneeskunde,
1999;143(45):2232-2236.
G. te Brake and N. Karssemeijer, "Single and multiscale detection of masses in digital mammograms",
IEEE Transactions on Medical Imaging,
1999;18(7):628-639.
W. Veldkamp and N. Karssemeijer, "Improved method for detection of microcalcification clusters in digital mammograms",
Medical Imaging,
1999;3661:512-522.
G. te Brake, M. Stoutjesdijk and N. Karssemeijer, "Discrete dynamic contour model for mass segmentation in digital mammograms",
Medical Imaging,
1999;3661:911-919.
N. Karssemeijer, "Local orientation distribution as a function of spatial scale for detection of masses in mammograms",
Information Processing in Medical Imaging,
1999;1613:280-293.
G. te Brake, N. Karssemeijer and J. Hendriks, "Automated detection of breast carcinomas not detected in a screening program",
Radiology,
1998;207(2):465-471.
J. Barentsz, G. Jager, P. van Vierzen, J. Witjes, S. Strijk, H. Peters, N. Karssemeijer and S. Ruijs, "Staging urinary bladder cancer after transurethral biopsy: value of fast dynamic contrast-enhanced MR imaging",
Radiology,
1996;201(1):185-193.
N. Karssemeijer and M. Thijssen, "Determination of contrast-detail curves of mammography systems by automated image analysis",
Digital Mammography,
1996;96:155-160.
N. Karssemeijer, "Adaptive noise equalization and recognition of microcalcification clusters in mammograms",
Int J Patt Recogn Artif Intell,
1993;7:1357-1375.
H. Nab, N. Karssemeijer, L. Erning and J. Hendriks, "Comparison of digital and conventional mammography: a ROC study of 270 mammograms",
Medical Informatics,
1992;17(2):125-131.
H. Nab, N. Karssemeijer, L. van Erning, A. Verbeek and J. Hendriks, "Digital mammography is very useful in mass screening of breast cancer",
Nederlands Tijdschrift voor Geneeskunde,
1990;134(49):2383-2387.
N. Karssemeijer, "A relaxation method for image segmentation using a spatially dependent stochastic model",
Pattern Recognition Letters,
1990;11(1):13 - 23.
N. Karssemeijer, L. van Erning and E. Eijkman, "Recognition of organs in CT-image sequences: a model guided approach",
Computers and Biomedical Research,
1988;21(5):434-448.
N. Karssemeijer and E. Eijkman, "Modelling and representation of myocardial perfusion images for the evaluation of diagnostic properties",
Medical and Biological Engineering and Computing,
1987;25(2):181-188.