PUBLICATIONS

Journal Publications

In Conference Proceedings

Abstracts

Theses

  • 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
  • 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.
  • 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.
  • Self-supervised Out-of-Distribution detection for medical imaging.
    R. Geurtjens, D. Peeters and C. Jacobs. 2023.