Publications of Colin Jacobs
2024
Papers in international journals
- D. Zhong, G. Sidorenkov, C. Jacobs, P. de Jong, H. Gietema, R. Stadhouders, K. Nackaerts, J. Aerts, M. Prokop, H. Groen, G. de Bock, R. Vliegenthart, M. Heuvelmans and S. Atzen, "Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial", Radiology, 2024;313.
- D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs, "Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation", European Radiology, 2024.
- E. Sogancioglu, B. van Ginneken, F. Behrendt, M. Bengs, A. Schlaefer, M. Radu, D. Xu, K. Sheng, F. Scalzo, E. Marcus, S. Papa, J. Teuwen, E. Scholten, S. Schalekamp, N. Hendrix, C. Jacobs, W. Hendrix, C. Sánchez and K. Murphy, "Nodule detection and generation on chest X-rays: NODE21 Challenge", IEEE Transactions on Medical Imaging, 2024;43(8):2839-2853.
- L. Boulogne, J. Charbonnier, C. Jacobs, E. van der Heijden and B. van Ginneken, "Estimating lung function from computed tomography at the patient and lobe level using machine learning", Medical Physics, 2024;51:2834-2845.
- C. Jacobs, "Decoding pulmonary nodules: can machine learning enhance malignancy risk stratification?", Thorax, 2024;79:293-294.
- W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Structure and position-aware graph neural network for airway labeling", Medical Image Analysis, 2024;97:103286.
- C. Ferreira, K. Venkadesh, C. Jacobs, M. Coimbra and A. Campilho, "Towards automatic forecasting of lung nodule diameter with tabular data and CT imaging", Biomedical Signal Processing and Control, 2024;96:106625.
Abstracts
- R. Dinnessen, K. Venkadesh, D. Peeters, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "External validation of an AI algorithm for pulmonary nodule malignancy risk estimation on a dataset of incidentally detected pulmonary nodules", European Congress of Radiology, 2024.
- F. van der Graaf, N. Antonissen, Z. Saghir, M. Prokop and C. Jacobs, "External validation of the Sybil risk model as a tool to identify low-risk individuals eligible for biennial lung cancer screening", European Congress of Radiology, 2024.
- D. Peeters, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs, "Towards safe and reliable implementation of AI models for nodule malignancy estimation using distance-based out-of-distribution detection", Annual Meeting of the European Society of Thoracic Imaging, 2024.
- F. van der Graaf, N. Antonissen, E. Scholten, M. Prokop and C. Jacobs, "Assessing the agreement between privacy-preserving Llama model and human experts when labelling radiology reports for specific significant incidental findings in lung cancer screening", Annual Meeting of the European Society of Thoracic Imaging, 2024.
- M. Vitale, M. Boenink, M. Vegter and C. Jacobs, "Norms for Responsible AI-enabled Population Screening", European Society for Philosophy of Medicine and Healthcare, 2024.
- N. Antonissen, K. Venkadesh, H. Gietema, R. Vliegenthart, Z. Saghir, E. Scholten, M. Prokop, C. Schaefer-Prokop and C. Jacobs, "Retrospective validation and comparison of deep learning based risk thresholds versus growth-centric protocols in pulmonary nodule assessment in screening", Annual Meeting of the European Society of Thoracic Imaging, 2024.
- B. Obreja, K. Venkadesh, W. Hendrix, Z. Saghir, M. Prokop and C. Jacobs, "Deep Learning for estimating pulmonary nodule malignancy risk: How much data does AI need to reach radiologist level performance?", European Congress of Radiology, 2024.
PhD theses
- G. Humpire-Mamani, "Deep Learning for Localization and Segmentation in Thorax Abdomen CT", PhD thesis, 2024.
- K. Venkadesh, "AI for lung cancer screening", PhD thesis, 2024.
- W. Hendrix, "Artificial Intelligence for Detection of Lung and Airway Nodules in Clinical Chest CT scans", PhD thesis, 2024.