activity
20162023
most citedOne Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis

11 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV20235 cited

HydraViT: Adaptive Multi-Branch Transformer for Multi-Label Disease Classification from Chest X-ray Images

Şaban Öztürk, M. Yiğit Turalı, Tolga Çukur

Chest X-ray is an essential diagnostic tool in the identification of chest diseases given its high sensitivity to pathological abnormalities in the lungs. However, image-driven dia…

eess.IV2023

CalibFPA: A Focal Plane Array Imaging System based on Online Deep-Learning Calibration

Alper Güngör, M. Umut Bahceci, Yasin Ergen +4

Compressive focal plane arrays (FPA) enable cost-effective high-resolution (HR) imaging by acquisition of several multiplexed measurements on a low-resolution (LR) sensor. Multiple…

eess.SP20234 cited

DreaMR: Diffusion-driven Counterfactual Explanation for Functional MRI

Hasan Atakan Bedel, Tolga Çukur

Deep learning analyses have offered sensitivity leaps in detection of cognitive states from functional MRI (fMRI) measurements across the brain. Yet, as deep models perform hierarc…

eess.IV2023

JointNET: A Deep Model for Predicting Active Sacroiliitis from Sacroiliac Joint Radiography

Sevcan Turk, Ahmet Demirkaya, M Yigit Turali +9

Purpose: To develop a deep learning model that predicts active inflammation from sacroiliac joint radiographs and to compare the success with radiologists. Materials and Methods: A…

cs.CL20223 cited

Unsupervised Simplification of Legal Texts

Mert Cemri, Tolga Çukur, Aykut Koç

The processing of legal texts has been developing as an emerging field in natural language processing (NLP). Legal texts contain unique jargon and complex linguistic attributes in…

eess.IV202211 cited

One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis

Onat Dalmaz, Usama Mirza, Gökberk Elmas +5

Multi-institutional collaborations are key for learning generalizable MRI synthesis models that translate source- onto target-contrast images. To facilitate collaboration, federate…