3 papers
cs.CV2026
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
cs.AI2026
Extending TotalSegmentator: Predicting Patient and Acquisition Characteristics from CT and MR Images
Jakob Wasserthal, Joshy Cyriac, Michael Bach +7
Background: Patient details and acquisition metadata are important for clinical decisions, image quality control, and automated research pipelines, but may be missing or unreliable…
cs.CV2024
Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI
Ashraya K. Indrakanti, Jakob Wasserthal, Martin Segeroth +6
Purpose: To develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysms (UICA) in 3D TOF-MRI, and compare models trai…