1 citations · 1 across the 3 of their papers we have counts for
3 papers
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…
A Hybrid AI-based and Rule-based Approach to DICOM De-identification: A Solution for the MIDI-B Challenge
Hamideh Haghiri, Rajesh Baidya, Stefan Dvoretskii +2
Ensuring the de-identification of medical imaging data is a critical step in enabling safe data sharing. This paper presents a hybrid de-identification framework designed to proces…
Medical Image De-Identification Benchmark Challenge
Linmin Pei, Granger Sutton, Michael Rutherford +67
The de-identification (deID) of protected health information (PHI) and personally identifiable information (PII) is a fundamental requirement for sharing medical images, particular…