Monthly DIAG News – August 2026

DIAG at MICCAI 2026

DIAG is getting ready for MICCAI 2026!" Our members are involved in a wide range of workshops and challenge organisations, oral presentations, and poster sessions! Below, you can find an overview of where to meet DIAG members at MICCAI this year.

One event we would particularly like to highlight the COMPAYL++ on September 27th. This full-day event brings together three MICCAI satellite events focused on computational pathology including the COMPAYL’26 workshop, the REG2 challenge, and a tutorial, featuring a keynote by Nadieh-Khalili.

On October 1, the Thoracic Image Analysis Workshop will bring together researchers working on a wide range of thoracic imaging applications. The workshop is co-organized by Colin Jacobs.

As always, DIAG members are (co-)organising challenges at MICCAI: 
The Breast Imaging Group MRI Challenge, co-organized by Henkjan Huisman, will take place on September 27. The challenge focuses on predicting breast cancer risk in women. 
On October 1, Learn2Reg, co-organized by Alessa Hering, will take place. This registration challenge introduces two tasks involving the registration of PET/CT images and inspiratory and expiratory chest CT scans.
The CHIMERA-Agent challenge will also take place on October 1. The challenge aims to develop a flexible AI agent for realistic clinical decision-making in prostate cancer biopsy.

DIAG members will also contribute to several presentations and programme activities at MICCAI. On September 30, Sarah de Boer and Hartmut-haentze will give oral presentations as part of the Open Data Track on the 30th of September (which is co-organized by Alessa Hering).

We are excited for MICCAI 2026 and look forward to seeing many of you in Strasbourg!

DIAG at ECP

DIAG members are orginazing the Computational Pathology Symposium at ECP in Stockholm this year. On the 13th of September Jeroen van der Laak and Frédérique Meeuwsen are organising an exciting event focused on computational pathology. This year a Mythbusters session will be hosted!

New DIAG members

We welcomed the following new members in August:

• Diletta Fioretti

• Jochem Bossenbroek

• Nynke Dijkhuis

• Alessia Moretti

• Kristina Hristova

• Paul Verhoeven

• Gonzalo de Toro

• Jasmijn van Rooden

• Tommaso Russo

Highlighted publications

R. Spaans, N. Khalili, G. Litjens and J. van Basten, "Tussen potentie en praktijk: AI als motor voor zorgtransformatie bij prostaatkanker", Tijdschrift voor Urologie, 2026.

Arab A, Garcia V, Kahaki S, van Rijthoven M, Salgado R, Gallas BD, Petrick N, Ciompi F, Chen W. Methodological considerations for evaluating deep learning segmentation models in digital pathology whole-slide images. J Med Imaging (Bellingham). 2026 May;13(3):037501. doi: 10.1117/1.JMI.13.3.037501. Epub 2026 Jun 12. PMID: 42305726; PMCID: PMC13267111.

T. Coelho, J.S. Bosma, V. Bozgo, C. Noordman, R. Grimm, M. de Rooij, M. Maas and H. Huisman, "Diagnostically Calibrated AI Image Quality Framework Applied to Prostate Cancer Detection at MRI", Radiology, 2026;320.

R. Dinnessen, N. Antonissen, D. Peeters, H. Gietema, M. Henkens, F. Mohamed Hoesein, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "Multicentre performance and consistency of two deep learning models for malignancy probability estimation of incidental pulmonary nodules", European Radiology, 2026.

J. Tagscherer, S. de Boer, F. van der Graaf, L. Philipp, C. Jacobs, E. Smit and A. Hering, "Systematic evaluation of foundation models for organ-level classification on CT scans", International Journal of Computer Assisted Radiology and Surgery, 2026.

J. Dixon-Douglas, D. Drubay, R. Salgado, B. Acs, J. van der Laak, Y. Yuan, M. Amgad, L. Cooper, Y. Hagos, K. AbdulJabbar, J. Meakin, B. van Ginneken, H. Yan, J. Lemonnier, F. Penault-Llorca, M. Lacroix-Triki, H. Joensuu, P. Kellokumpu-Lehtinen, S. Loibl, C. Denkert, G. Viale, M. Colleoni, C. Sotiriou, M. Piccart, M. Dieci, S. Demaria, R. Kammler, A. Wolff, J. Sparano, S. Adams, S. Badve, R. Gray, G. Curigliano, A. Salomon, T. Nielsen, L. Pusztai, F. Ciompi, S. Michiels and S. Loi, "Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study", The Lancet Oncology, 2026;27:1181-1192.

N. Uysal, C. Grisi, K. Faryna, J. van Ipenburg and G. Litjens, "Towards patient-level Gleason grading from AI-based analysis of individual sections", Scientific Reports, 2026.

A. Bouwmeester, T. Gootzen, M. Nobbenhuis, V. Rudaitis, C. van den Berg, H. van Beekhuizen, L. Alcalá, D. Smedts, N. Visser, V. Verhoef, T. Jonges, R. Zweemer, A. Leon-Catillo, C. Lems, J. de Hullu, J. van der Laak, M. Steenbeek and M. Simons, "Additional sectioning and AI -assisted diagnosis reveal underdiagnosis of serous (pre)malignancies in fallopian tube specimen from BRCA 1/2 carriers", Histopathology, 2026.

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