Home Page

I am a scientist with more than 15 years of experience in medical image analysis and computer vision, working at the intersection of pathology, oncology, and artificial intelligence. As an Associate Professor of computational pathology, I lead a multidisciplinary team in the pathology department of the Radboud University Medical Center, working on precision oncology, developing artificial intelligence models to better understand diseases, discover novel biomarkers, and help physicians to improve their routine diagnostics and to select the right treatments to help patients.

New publications

[26/04/2024] Siem de Jong, Marie Louise Groot, Roel L. J. Verhoeven, Erik H. F. M. van der Heijden, Francesco Ciompi, "Weakly supervised lung cancer detection on label-free intraoperative microscopy with higher harmonic generation", Medical Imaging with Deep Learning (MIDL), 2024 [accepted].

[26/04/2024] Agata Polejowska, Fazael Ayatollahi, Ayse Selcen Oguz Erdogan, Francesco Ciompi, Annemarie Boleij, "Spirochetosis detection in colon histopathology images via fine-tuning and boosting techniques using foundation models", Medical Imaging with Deep Learning (MIDL), 2024 [accepted].

[24/04/2024] Esther M.M. Smeets, Marija Trajkovic-Arsic, Daan Geijs, Sinan Karakaya, Monica van Zanten, Lodewijk A.A. Brosens, Benedikt Feuerecker, Martin Gotthardt, Jens T. Siveke, Rickmer Braren, Francesco Ciompi and Erik H.J.G. Aarntzen, "Histology-based radiomics for [18F]FDG-PET identifies tissue heterogeneity in pancreatic cancer", Journal of Nuclear Medicine, 2024 [accepted].

[05/02/2024] Nohemi S. Leon Contreras, Clément Grisi, Witali Aswolinskiy, Simona Vatrano, Filippo Fraggetta, Iris Nagtegaal, Marina D’Amato and Francesco Ciompi, "Benchmarking hierarchical image pyramid transformer for the classification of colon biopsies and polyps histopathology images", IEEE International Symposium on Biomedical Imaging (ISBI), 2024 [accepted].

[05/02/2024] Cristian Tommasino, Cristiano Russo, Antonio Maria Rinaldi and Francesco Ciompi, "HoVer-UNet: Accelerating HoVerNet with UNet-based multi-class nuclei segmentation via knowledge distillation", IEEE International Symposium on Biomedical Imaging (ISBI), 2024 [accepted].

[05/02/2024] Carlijn M. Lems, Daan J. Geijs, John-Melle Bokhorst, Maxime Sülter, Leander van Eekelen and Francesco Ciompi, "Color deconvolution for color-agnostic and cross-modality analysis of immunohistochemistry whole-slide images with deep learning", IEEE International Symposium on Biomedical Imaging (ISBI), 2024 [accepted].