4 papers
Information Bottleneck Attribution for Visual Explanations of Diagnosis and Prognosis
Ugur Demir, Ismail Irmakci, Elif Keles +7
Visual explanation methods have an important role in the prognosis of the patients where the annotated data is limited or unavailable. There have been several attempts to use gradi…
Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI
Syed Muhammad Anwar, Ismail Irmakci, Drew A. Torigian +5
Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful for clinical and rese…
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset
Arjun D. Desai, Francesco Caliva, Claudia Iriondo +26
Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthriti…
Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans
Yucheng Liu, Naji Khosravan, Yulin Liu +5
Creating large scale high-quality annotations is a known challenge in medical imaging. In this work, based on the CycleGAN algorithm, we propose leveraging annotations from one mod…