Publications

2021

Papers in international journals

1. L. van Eekelen, H. Pinckaers, M. van den Brand, K. Hebeda and G. Litjens, "Using deep learning for quantification of cellularity and cell lineages in bone marrow biopsies and comparison to normal age-related variation.", Pathology, 2021.
   Abstract DOI PMID Download
2. K. Kartasalo, W. Bulten, B. Delahunt, P. Chen, H. Pinckaers, H. Olsson, X. Ji, N. Mulliqi, H. Samaratunga, T. Tsuzuki, J. Lindberg, M. Rantalainen, C. Wahlby, G. Litjens, P. Ruusuvuori, L. Egevad and M. Eklund, "Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps.", European Urology Focus, 2021;7(4):687-691.
   Abstract DOI PMID Download
3. E. Munari, M. Marconi, G. Querzoli, G. Lunardi, P. Bertoglio, F. Ciompi, A. Tosadori, A. Eccher, N. Tumino, L. Quatrini, P. Vacca, G. Rossi, A. Cavazza, G. Martignoni, M. Brunelli, G. Netto, L. Moretta, G. Zamboni and G. Bogina, "Impact of PD-L1 and PD-1 Expression on the Prognostic Significance of CD8+, Tumor-Infiltrating Lymphocytes in Non-Small Cell Lung Cancer.", Frontiers in immunology, 2021;12:680973.
   Abstract DOI PMID Download
4. E. Munari, F. Mariotti, L. Quatrini, P. Bertoglio, N. Tumino, P. Vacca, A. Eccher, F. Ciompi, M. Brunelli, G. Martignoni, G. Bogina and L. Moretta, "PD-1/PD-L1 in Cancer: Pathophysiological, Diagnostic and Therapeutic Aspects.", International journal of molecular sciences, 2021;22(10).
   Abstract DOI PMID
5. M. Hermsen, V. Volk, J. Brasen, D. Geijs, W. Gwinner, J. Kers, J. Linmans, N. Schaadt, J. Schmitz, E. Steenbergen, Z. Swiderska-Chadaj, B. Smeets, L. Hilbrands and J. van der Laak, "Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning", Laboratory Investigation, 2021;101(8):970-982.
   Abstract DOI PMID Download
6. J. van der Laak, G. Litjens and F. Ciompi, "Deep learning in histopathology: the path to the clinic.", Nature Medicine, 2021;27(5):775-784.
   Abstract DOI PMID Download
7. F. Faita, T. Oranges, N. Di Lascio, F. Ciompi, S. Vitali, G. Aringhieri, A. Janowska, M. Romanelli and V. Dini, "Ultra-high-frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions.", Experimental Dermatology, 2021.
   Abstract DOI PMID Download
8. H. Pinckaers, W. Bulten, J. der Van Laak and G. Litjens, "Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels.", IEEE Transactions on Medical Imaging, 2021.
   Abstract DOI PMID Download
9. 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.
   Abstract DOI PMID Download
10. M. Balkenhol, F. Ciompi, Z. Swiderska-Chadaj, R. van de Loo, M. Intezar, I. Otte-Holler, D. Geijs, J. Lotz, N. Weiss, T. de Bel, G. Litjens, P. Bult and J. van der Laak, "Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics.", The Breast, 2021;56:78-87.
    Abstract DOI PMID
11. O. Turner, B. Knight, A. Zuraw, G. Litjens and D. Rudmann, "Mini Review: The Last Mile-Opportunities and Challenges for Machine Learning in Digital Toxicologic Pathology.", Toxicologic Pathology, 2021;49(4):714-719.
    Abstract DOI PMID Download
12. M. van Rijthoven, M. Balkenhol, K. Silina, J. van der Laak and F. Ciompi, "HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images", Medical Image Analysis, 2021;68:101890.
    Abstract DOI PMID Algorithm Download
13. N. Lessmann, C. Sánchez, L. Beenen, L. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. van Everdingen, P. Gerke, B. Geurts, H. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken, "Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence", Radiology, 2021;298(1):E18-E28.
    Abstract DOI PMID Algorithm Download
14. D. Tellez, G. Litjens, J. van der Laak and F. Ciompi, "Neural Image Compression for Gigapixel Histopathology Image Analysis.", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021;43(2):567-578.
    Abstract DOI PMID Download
15. J. Bogaerts, M. Steenbeek, M. van Bommel, J. Bulten, J. van der Laak, J. de Hullu and M. Simons, "Recommendations for diagnosing STIC: a systematic review and meta-analysis", 2021;480(4):725-737.
    Abstract DOI Download
16. F. Ciompi, M. Veta, J. van der Laak and N. Rajpoot, "Editorial Computational Pathology", IEEE} Journal of Biomedical and Health Informatics, 2021;25(2):303-306.
    Abstract DOI
17. N. Marini, S. Otálora, D. Podareanu, M. van Rijthoven, J. van der Laak, F. Ciompi, H. Muller and M. Atzori, "Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images", Frontiers in Computer Science, 2021;3.
    Abstract DOI

Preprints

1. A. Reinke, M. Eisenmann, M. Tizabi, C. Sudre, T. Radsch, M. Antonelli, T. Arbel, S. Bakas, M. Cardoso, V. Cheplygina, K. Farahani, B. Glocker, D. Heckmann-Notzel, F. Isensee, P. Jannin, C. Kahn, J. Kleesiek, T. Kurc, M. Kozubek, B. Landman, G. Litjens, K. Maier-Hein, B. Menze, H. Muller, J. Petersen, M. Reyes, N. Rieke, B. Stieltjes, R. Summers, S. Tsaftaris, B. van Ginneken, A. Kopp-Schneider, P. Jager and L. Maier-Hein, "Common Limitations of Image Processing Metrics: A Picture Story", arXiv preprint arXiv:2104.05642, 2021.
   Abstract arXiv
2. M. Antonelli, A. Reinke, S. Bakas, K. Farahani, AnnetteKopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, B. van Ginneken, M. Bilello, P. Bilic, P. Christ, R. Do, M. Gollub, S. Heckers, H. Huisman, W. Jarnagin, M. McHugo, S. Napel, J. Pernicka, K. Rhode, C. Tobon-Gomez, E. Vorontsov, H. Huisman, J. Meakin, S. Ourselin, M. Wiesenfarth, P. Arbelaez, B. Bae, S. Chen, L. Daza, J. Feng, B. He, F. Isensee, Y. Ji, F. Jia, N. Kim, I. Kim, D. Merhof, A. Pai, B. Park, M. Perslev, R. Rezaiifar, O. Rippel, I. Sarasua, W. Shen, J. Son, C. Wachinger, L. Wang, Y. Wang, Y. Xia, D. Xu, Z. Xu, Y. Zheng, A. Simpson, L. Maier-Hein and M. Cardoso, "The Medical Segmentation Decathlon", arXiv preprint arXiv:2106.05735, 2021.
   Abstract arXiv

Papers in conference proceedings

1. A. Saha, J. Bosma, J. Linmans, M. Hosseinzadeh and H. Huisman, "Anatomical and Diagnostic Bayesian Segmentation in Prostate MRI -- Should Different Clinical Objectives Mandate Different Loss Functions?", Medical Imaging Meets NeurIPS Workshop - 35th Conference on Neural Information Processing Systems (NeurIPS), 2021.
   Abstract arXiv
2. G. Smit, F. Ciompi, M. Cigéhn, A. Bodén, J. van der Laak and C. Mercan, "Quality control of whole-slide images through multi-class semantic segmentation of artifacts", Medical Imaging with Deep Learning, 2021.
   Abstract Url
3. A. Reinke, M. Eisenmann, M. Tizabi, C. Sudre, T. Radsch, M. Antonelli, T. Arbel, S. Bakas, J. Cardoso, V. Cheplygina, K. Farahani, B. Glocker, D. Heckmann-Notzel, F. Isensee, P. Jannin, C. Kahn, J. Kleesiek, T. Kurc, M. Kozubek, B. Landman, G. Litjens, K. Maier-Hein, A. Martel, H. Muller, J. Petersen, M. Reyes, N. Rieke, B. Stieltjes, R. Summers, S. Tsaftaris, B. van Ginneken, A. Kopp-Schneider, P. Jager and L. Maier-Hein, "Common limitations of performance metrics in biomedical image analysis", Medical Imaging with Deep Learning, 2021.
   Abstract DOI
4. N. Marini, S. Otalora, F. Ciompi, G. Silvello, S. Marchesin, S. Vatrano, G. Buttafuoco, M. Atzori, H. Muller, N. Burlutskiy, Z. Li, F. Minhas, T. Peng, N. Rajpoot, B. Torbennielsen, J. Der Van Laak, M. Veta, Y. Yuan and I. Zlobec, "Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations", 2021.
   Abstract
5. D. Geijs, H. Pinckaers, A. Amir and G. Litjens, "End-to-end classification on basal-cell carcinoma histopathology whole-slides images", Medical Imaging, 2021;11603:1160307.
   Abstract DOI
6. J. Vermazeren, L. van Eekelen, L. Meesters, M. Looijen-Salamon, S. Vos, E. Munari, C. Mercan and F. Ciompi, "muPEN: Multi-class PseudoEdgeNet for PD-L1 assessment", Medical Imaging with Deep Learning, 2021.
   Abstract Url
7. W. Aswolinskiy, D. Tellez, G. Raya, L. van der Woude, M. Looijen-Salamon, J. van der Laak, K. Grunberg and F. Ciompi, "Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images", Medical Imaging 2021: Digital Pathology, 2021;11603:1 - 7.
   Abstract DOI
8. M. van Rijthoven, M. Balkenhol, M. Atzori, P. Bult, J. van der Laak and F. Ciompi, "Few-shot weakly supervised detection and retrieval in histopathology whole-slide images", Medical Imaging, 2021;11603:137 - 143.
   Abstract DOI
9. K. Faryna, J. van der Laak and G. Litjens, "Tailoring automated data augmentation to H&E-stained histopathology", Medical Imaging with Deep Learning, 2021.
   Abstract Url
10. R. Fick, B. Tayart, C. Bertrand, S. Lang, T. Rey, F. Ciompi, C. Tilmant, I. Farre and S. Hadj, "A Partial Label-Based Machine Learning Approach For Cervical Whole-Slide Image Classification: The Winning TissueNet Solution", 2021 43rd Annual International Conference of the {IEEE} Engineering in Medicine and Biology Society ({EMBC}), 2021.
    Abstract DOI

Abstracts

1. Y. Jiao, M. Rijthoven, J. Li, K. Grunberg, S. Fei and F. Ciompi, "Automatic Lung Cancer Segmentation in Histopathology Whole-Slide Images with Deep Learning", European Congress on Digital Pathology (ECDP), 2021.
   Abstract

PhD theses

1. D. Tellez, "Advancing computational pathology with deep learning: from patches to gigapixel image-level classification", PhD thesis, 2021.
   Abstract Url