activity
20192025
most citedSemi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

19 citations · 20 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2025

Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm

Hongyi Pan, Gorkem Durak, Elif Keles +27

Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. Intraductal papillary mucinous neoplasms (IPMNs), key cancer precursors,…

eess.IV2025

Predicting Risk of Pulmonary Fibrosis Formation in PASC Patients

Wanying Dou, Gorkem Durak, Koushik Biswas +14

While the acute phase of the COVID-19 pandemic has subsided, its long-term effects persist through Post-Acute Sequelae of COVID-19 (PASC), commonly known as Long COVID. There remai…

cs.CY2024★ 1 cited

Ethical Framework for Responsible Foundational Models in Medical Imaging

Debesh Jha, Gorkem Durak, Abhijit Das +33

The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. Th…

eess.IV2021

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…

eess.IV2020★ 19 cited

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…

eess.IV2020

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…

eess.IV2019

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…