P. Vendittelli, J. Bokhorst, E. Smeets, V. Kryklyva, L. Brosens, C. Verbeke and G. Litjens, "Automatic quantification of tumor-stroma ratio as a prognostic marker for pancreatic cancer",
PLOS ONE,
2024;19:e0301969.
C. Lems, D. Geijs, J. Bokhorst, M. Sülter, L. van Eekelen and F. Ciompi, "Color Deconvolution for Color-Agnostic and Cross-Modality Analysis of Immunohistochemistry Whole-Slide Images with Deep Learning",
2024 IEEE International Symposium on Biomedical Imaging (ISBI),
2024:1-4.
N. Brouwer, A. Khan, J. Bokhorst, F. Ayatollahi, J. Hay, F. Ciompi, F. Simmer, N. Hugen, J. de Wilt, M. Berger, A. Lugli, I. Zlobec, J. Edwards and I. Nagtegaal, "The complexity of shapes; how the circularity of tumor nodules impacts prognosis in colorectal cancer",
Modern Pathology,
2023:100376.
J. Bokhorst, I. Nagtegaal, F. Fraggetta, S. Vatrano, W. Mesker, M. Vieth, J. van der Laak and F. Ciompi, "Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images",
Scientific Reports,
2023;13:8398.
J. Bokhorst, I. Nagtegaal, I. Zlobec, H. Dawson, K. Sheahan, F. Simmer, R. Kirsch, M. Vieth, A. Lugli, J. van der Laak and F. Ciompi, "Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer",
Cancers,
2023;15(7):2079.
J. Bokhorst, F. Ciompi, S. Öztürk, A. Oguz Erdogan, M. Vieth, H. Dawson, R. Kirsch, F. Simmer, K. Sheahan, A. Lugli, I. Zlobec, J. van der Laak and I. Nagtegaal, "Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer",
Modern Pathology,
2023;36:100233.
M. Smit, F. Ciompi, J. Bokhorst, G. van Pelt, O. Geessink, H. Putter, R. Tollenaar, J. van Krieken, W. Mesker and J. van der Laak, "Deep learning based tumor-stroma ratio scoring in colon cancer correlates with microscopic assessment",
Journal of Pathology Informatics,
2023.
P. Vendittelli, J. Bokhorst, E. Smeets, V. Kryklyva, L. Brosens, C. Verbeke and G. Litjens, "Automatic quantification of TSR as a prognostic marker for pancreatic cancer.",
Medical Imaging with Deep Learning,
2023.
C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. Horlings, W. Weichert, J. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J. Bokhorst, J. van der Laak and F. Ciompi, "Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer.",
NPJ breast cancer,
2022;8(1):120.
N. Marini, S. Marchesin, S. Otalora, M. Wodzinski, A. Caputo, M. van Rijthoven, W. Aswolinskiy, J. Bokhorst, D. Podareanu, E. Petters, S. Boytcheva, G. Buttafuoco, S. Vatrano, F. Fraggetta, J. van der Laak, M. Agosti, F. Ciompi, G. Silvello, H. Muller and M. Atzori, "Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.",
NPJ digital medicine,
2022;5(1):102.
L. Studer, J. Bokhorst, F. Ciompi, A. Fischer and H. Dawson, "Building-T-cell score is a potential predictor for more aggressive treatment in pT1 colorectal cancers",
Proceedings of the ECDP 2022 18th European Congress on Digital Pathology,
2022.
T. Haddad, A. Lugli, S. Aherne, V. Barresi, B. Terris, J. Bokhorst, S. Brockmoeller, M. Cuatrecasas, F. Simmer, H. El-Zimaity, J. Fléjou, D. Gibbons, G. Cathomas, R. Kirsch, T. Kuhlmann, C. Langner, M. Loughrey, R. Riddell, A. Ristimäki, S. Kakar, K. Sheahan, D. Treanor, J. van der Laak, M. Vieth, I. Zlobec and I. Nagtegaal, "Improving tumor budding reporting in colorectal cancer: a Delphi consensus study",
Virchows Archiv,
2021;479:459-469.
T. de Bel, J. Bokhorst, J. van der Laak and G. Litjens, "Residual cyclegan for robust domain transformation of histopathological tissue slides.",
Medical Image Analysis,
2021;70:102004.
J. Bokhorst, I. Nagtegaal, F. Fraggetta, S. Vatrano, W. Mesker, M. Vieth, J. van der Laak and F. Ciompi, "Automated risk classification of colon biopsies based on semantic segmentation of histopathology images",
arXiv:2109.07892,
2021.
J. Bokhorst, F. Ciompi, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, J. van der Laak and I. Nagtegaal, "Computer-assisted hot-spot selection for tumor budding assessment in colorectal cancer",
European Congress of Pathology,
2020.
J. Bokhorst, I. Nagtegaal, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, J. van der Laak and F. Ciompi, "Deep learning based tumor bud detection in pan-cytokeratin stained colorectal cancer whole-slide images",
European Congress of Pathology,
2020.
L. Studer, J. Bokhorst, I. Zlobec, A. Lugli, A. Fischer, F. Ciompi, J. van der Laak, I. Nagtegaal and H. Dawson, "Validation of computer-assisted tumour-bud and T-cell detection in pT1 colorectal cancer",
European Congress of pathology,
2020.
J. Bokhorst, A. Blank, A. Lugli, I. Zlobec, H. Dawson, M. Vieth, L. Rijstenberg, S. Brockmoeller, M. Urbanowicz, J. Flejou, R. Kirsch, F. Ciompi, J. van der Laak and I. Nagtegaal, "Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning",
Modern Pathology,
2019.
D. Tellez, G. Litjens, P. Bándi, W. Bulten, J. Bokhorst, F. Ciompi and J. van der Laak, "Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology",
Medical Image Analysis,
2019;58:101544.
J. Bokhorst, H. Pinckaers, P. van Zwam, I. Nagetgaal, J. van der Laak and F. Ciompi, "Learning from sparsely annotated data for semantic segmentation in histopathology images",
Medical Imaging with Deep Learning,
2019;102:81-94.
J. Bokhorst, H. Dawson, A. Blank, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, M. Urbanowicz, S. Brockmoeller, J. Flejou, L. Rijstenberg, J. van der Laak, F. Ciompi and I. Nagtegaal, "Assessment of tumor buds in colorectal cancer. A large-scale international digital observer study",
European Congress of Pathology,
2019.
T. Haddad, N. Farahani, J. Bokhorst, F. Doubrava-Simmer, F. Ciompi, I. Nagtegaal and J. van der Laak, "A Colorectal Carcinoma in 3D: Merging Knife-Edge Scanning Microscopy and Deep Learning",
EACR,
2019.
J. Bokhorst, L. Rijstenberg, D. Goudkade, I. Nagtegaal, J. van der Laak and F. Ciompi, "Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning",
Computational Pathology and Ophthalmic Medical Image Analysis,
2018.