Publications

2022

  1. The Future of Artificial Intelligence Applied to Immunotherapy Trials
    Neoadjuvant Immunotherapy Treatment of Localized Genitourinary Cancers
    Z. Bodalal, S. Trebeschi, I. Wamelink, K. G. Lipman, T. Bucho, N. Van Dijk, T. Boellaard, S. Waktola, R. G. H. Beets-Tan, 2022
    doi
    Abstract
  2. Breast imaging and deep learning: past, present, and future
    Advances in Magnetic Resonance Technology and Applications
    S. Eskreis-Winkler, J. Teuwen, S. Benson, 2022
    doi
    Abstract
  3. Ovarian imaging radiomics quality score assessment: an EuSoMII radiomics auditing group initiative
    European Radiology
    A. Ponsiglione, A. Stanzione, G. Spadarella, A. Baran, L. A. Cappellini, K. G. Lipman, P. Van Ooijen, R. Cuocolo, 2022, 33;(3):2239-2247
    doi paper (open access)
    Abstract
  4. Intracerebral Hemorrhage Segmentation on Noncontrast Computed Tomography Using a Masked Loss Function U-Net Approach
    Journal of Computer Assisted Tomography
    N. A. Coorens, K. G. Lipman, S. P. Krishnam, C. O. Tan, L. Alic, R. Gupta, 2022, 47;(1):93-101
    doi paper (open access)
    Abstract

2021

  1. An improved automatic system for aiding the detection of colon polyps using deep learning
    2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)
    L. Cai, R. Beets-Tan, S. Benson, 2021
    doi paper (open access)
    Abstract
  2. Artificial intelligence-mediated diagnosis of asbestosis
    ILD / DPLD of known origin
    K. B. W. G. Lipman, C. J. De Gooijer, T. N. Boellaard, F. Van Der Heijden, R. G. H. Beets-Tan, Z. Bodalal, S. Trebeschi, S. Burgers, 2021
    doi
    Abstract
  3. Pleural plaque volume correlation to lung function and artificial intelligence-driven pleural plaque quantification
    ILD / DPLD of known origin
    K. B. W. G. Lipman, T. N. Boellaard, C. J. De Gooijer, N. Bogveradze, E. K. Hong, F. Landolfi, F. Castagnoli, L. C. Cavallo, N. Lebedyeva, F. Van Der Heijden, R. G. H. Beets-Tan, Z. Bodalal, S. Burgers, S. Trebeschi, 2021
    doi
    Abstract
  4. Prognostic Value of Deep Learning-Mediated Treatment Monitoring in Lung Cancer Patients Receiving Immunotherapy
    Frontiers in Oncology
    S. Trebeschi, Z. Bodalal, T. N. Boellaard, T. M. Tareco Bucho, S. G. Drago, I. Kurilova, A. M. Calin-Vainak, A. Delli Pizzi, M. Muller, K. Hummelink, K. J. Hartemink, T. D. L. Nguyen-Kim, E. F. Smit, H. J. W. L. Aerts, R. G. H. Beets-Tan, 2021, 11
    doi paper (open access)
    Abstract
  5. Development of a Prognostic AI-Monitor for Metastatic Urothelial Cancer Patients Receiving Immunotherapy
    Frontiers in Oncology
    S. Trebeschi, Z. Bodalal, N. Van Dijk, T. N. Boellaard, P. Apfaltrer, T. M. Tareco Bucho, T. D. L. Nguyen-Kim, M. S. Van Der Heijden, H. J. W. L. Aerts, R. G. H. Beets-Tan, 2021, 11
    doi paper (open access)
    Abstract
  6. The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation
    Surgical Endoscopy
    H. E. Haak, X. Gao, M. Maas, S. Waktola, S. Benson, R. G. H. Beets-Tan, G. L. Beets, M. Van Leerdam, J. Melenhorst, 2021, 36;(5):3592-3600
    doi paper (open access)
    Abstract
  7. Novel Breast Specimen Orientation Approach through 3D Visualizations for Relocating Inadequate Margins based on the Surgical Clips: Feasibility Study.
    R. F. V. Doremalen, K. B. G. Lipman, E. V. '. Riet, H. Torrenga, M. M. Smits, F. V. D. Heijden, 2021
    doi
    Abstract
  8. Creating small but meaningful representations of digital pathology images
    Proceedings of the MICCAI Workshop on Computational Pathology
    C. Guérendel, P. Arnold, B. Torben-Nielsen, 2021
    url
    Abstract