Publications of Henkjan Huisman

2022

Papers in international journals

1. M. Antonelli, A. Reinke, S. Bakas, K. Farahani, A. Kopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, B. van Ginneken, M. Bilello, P. Bilic, P. Christ, R. Do, M. Gollub, S. Heckers, H. Huisman, W. Jarnagin, M. McHugo, S. Napel, J. Pernicka, K. Rhode, C. Tobon-Gomez, E. Vorontsov, J. Meakin, S. Ourselin, M. Wiesenfarth, P. Arbelaez, B. Bae, S. Chen, L. Daza, J. Feng, B. He, F. Isensee, Y. Ji, F. Jia, I. Kim, K. Maier-Hein, D. Merhof, A. Pai, B. Park, M. Perslev, R. Rezaiifar, O. Rippel, I. Sarasua, W. Shen, J. Son, C. Wachinger, L. Wang, Y. Wang, Y. Xia, D. Xu, Z. Xu, Y. Zheng, A. Simpson, L. Maier-Hein and M. Cardoso, "The Medical Segmentation Decathlon", Nature Communications, 2022;13(1):4128.
   Abstract DOI PMID Cited by ~489
2. J. Bleker, T. Kwee, D. Rouw, C. Roest, J. Borstlap, I. de Jong, R. Dierckx, H. Huisman and D. Yakar, "A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics", European Radiology, 2022;32:6526-6535.
   Abstract DOI PMID
3. C. Roest, T. Kwee, A. Saha, J. Futterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Radiology, 2022.
   Abstract DOI Cited by ~7
4. M. Sunoqrot, A. Saha, M. Hosseinzadeh, M. Elschot and H. Huisman, "Artificial Intelligence for Prostate MRI: Open Datasets, Available Applications, and Grand Challenges", European Radiology Experimental, 2022:35.
   Abstract DOI Cited by ~26
5. L. Hadjiiski, K. Cha, H. Chan, K. Drukker, L. Morra, J. Nappi, B. Sahiner, H. Yoshida, Q. Chen, T. Deserno, H. Greenspan, H. Huisman, Z. Huo, R. Mazurchuk, N. Petrick, D. Regge, R. Samala, R. Summers, K. Suzuki, G. Tourassi, D. Vergara and S. III, "AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging", Medical Physics, 2022.
   Abstract DOI Cited by ~17
6. N. Alves, M. Schuurmans, G. Litjens, J.S. Bosma, J. Hermans and H. Huisman, "Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography", Cancers, 2022:376.
   Abstract DOI Download Cited by ~31
7. M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging", Cancers, 2022:3498.
   Abstract DOI Cited by ~2
8. S. Labus, M. Altmann, H. Huisman, A. Tong, T. Penzkofer, M. Choi, I. Shabunin, D. Winkel, P. Xinga, D. Szolar, S. Shea, R. Grimm, H. von Busch, A. Kamen, T. Herold and C. Baumann, "A concurrent, deep learning-based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists", European Radiology, 2022.
   Abstract DOI Cited by ~11

Papers in conference proceedings

1. Y. Li, Y. Fu, Q. Yang, Z. Min, W. Yan, H. Huisman, D. Barratt, V. Prisacariu and Y. Hu, "FEW-SHOT Image Segmentation for Cross-Institution Male Pelvic Organs Using Registration-Assisted Prototypical Learning", 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022.
   Abstract DOI Cited by ~10

Abstracts

1. S. Fransen, C. Roest, Q. van Lohuizen, J. Bosma, T. Kwee, D. Yakar and H. Huisman, "Diagnostic AI to speed up MRI protocols by identifying redundant sequences: are all diffusion-weighted prostate MRI sequences necessary?", Annual Meeting of the Radiological Society of North America, 2022.
   Abstract
2. N. Alves, J.S. Bosma and H. Huisman, "Towards Safe Clinical Use of Artificial Intelligence for Cancer Detection Through Uncertainty Quantification", Annual Meeting of the Radiological Society of North America, 2022.
   Abstract
3. M. Schuurmans, N. Alves, H. Huisman and J. Hermans, "Deep Learning for Detection of Iso-attenuating Pancreatic Adenocarcinoma in Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
   Abstract
4. J.S. Bosma, N. Alves and H. Huisman, "Performant and Reproducible Deep Learning Based Cancer Detection Models for Medical Imaging", Annual Meeting of the Radiological Society of North America, 2022.
   Abstract
5. T. Perik, J. Hermans and H. Huisman, "AI-assisted analysis of CT perfusion to predict response in patients with pancreatic adenocarcinoma", European Congress of Radiology, 2022.
   Abstract
6. S. de Jong, N. Alves, M. Schuurmans, J. Hermans and H. Huisman, "Deep Learning for Automatic Contrast Enhancement Phase Detection on Abdominal Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
   Abstract
7. C. Roest, T. Kwee, A. Saha, J. Futterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Congress of Radiology, 2022.
   Abstract
8. A. Saha, J.S. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", Annual Meeting of the Radiological Society of North America, 2022.
   Abstract

Master theses

1. S. Adilina, A. Saha and H. Huisman, "Domain Generalization for Prostate Cancer Detection in MRI", Master thesis, 2022.
   Abstract Url