3 papers
cs.CV2026
Sharing standardized image-derived data in computational pathology using DICOM
Daniela P. Schacherer, Christopher P. Bridge, David Clunie +13
Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into co…
cs.LG2025
From Data to Diagnosis: A Large, Comprehensive Bone Marrow Dataset and AI Methods for Childhood Leukemia Prediction
Henning Höfener, Farina Kock, Martina Pontones +9
Leukemia diagnosis primarily relies on manual microscopic analysis of bone marrow morphology supported by additional laboratory parameters, making it complex and time consuming. Wh…
eess.IV2025
Whole Slide Concepts: A Supervised Foundation Model For Pathological Images
Till Nicke, Daniela Schacherer, Jan Raphael Schäfer +6
Foundation models (FMs) are transforming computational pathology by offering new ways to analyze histopathology images. However, FMs typically require weeks of training on large da…