PUBLICATIONS

Journal Publications

Conference Proceedings

Theses

  • Performance of a screening-trained DL model for pulmonary nodule malignancy estimation of incidental clinical nodules
    R. Dinnessen, D. Peeters, N. Antonissen, F. Mohamed Hoesein, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs. European Radiology, 2025. doi.org/10.1007/s00330-025-11829-1
  • Towards safe and reliable deep learning for lung nodule malignancy estimation using out-of-distribution detection
    D. Peeters, K.V. Venkadesh, R. Dinnessen, Z. Saghir, E.T. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs. Computers in Biology and Medicine, 2025. doi.org/10.1016/j.compbiomed.2024.109633
  • Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation
    D. Peeters, N. Alves, K.V. Venkadesh, R. Dinnessen, Z. Saghir, E.T. Scholten, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs. European Radiology, 2023. doi.org/10.1007/s00330-024-10714-7
  • Benchmarking of Artificial Intelligence and Radiologists for Lung Cancer Screening in CT: The LUNA25 Challenge.
    D. Peeters, B. Obreja, N. Antonissen, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs. Annual Meeting of the Medical Image Computing and Computer Assisted Intervention Society, 2025.
  • Exploring AI-enabled nodule management for incidentally detected pulmonary nodules on CT.
    R. Dinnessen, A. Antonissen, D. Peeters, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs. Annual Meeting of the European Society of Thoracic Imaging, 2025.
  • Benchmarking of Artificial Intelligence and Radiologists for Lung Cancer Screening in CT: The LUNA25 Challenge.
    D. Peeters, B. Obreja, N. Antonissen, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs. European Congress of Radiology, 2025.
  • Towards safe and reliable implementation of AI models for nodule malignancy estimation using distance-based out-of-distribution detection.
    D. Peeters, K.V. Venkadesh, R. Dinnessen, Z. Saghir, E.T. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs. Annual Meeting of the European Society of Thoracic Imaging, 2024.
  • External validation of an AI algorithm for pulmonary nodule malignancy risk estimation on a dataset of incidentally detected pulmonary nodules.
    R. Dinnessen, K. Venkadesh, D. Peeters, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs. European Congress of Radiology, 2024.
  • The effect of applying an uncertainty estimation method on the performance of a deep learning model for nodule malignancy risk estimation.
    D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, H. Huisman, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs. European Congress of Radiology, 2023.
  • Reproducibility of Training Deep Learning Models for Medical Image Analysis
    J. Bosma, D. Peeters, N. Alves, A. Saha, Z. Saghir, C. Jacobs and H. Huisman. Medical Imaging with Deep Learning, 2023.
  • Self-supervised Out-of-Distribution detection for medical imaging.
    R. Geurtjens, D. Peeters and C. Jacobs. 2023.