6 papers
Masked and Predictive Self-Supervised Foundation Models for 3D Brain MRI
Esra Ergün, Hersh Chandarana, Dan Sodickson +1
Self-supervised foundation models have shown strong promise in medical imaging. However, existing MRI foundation-model studies have primarily emphasized segmentation and dense pred…
L-TGVN: Leveraging Longitudinal Priors for Personalized Rapid MRI
Arda Atalık, Sumit Chopra, Daniel K. Sodickson
MRI provides excellent soft-tissue contrast without ionizing radiation, but long acquisition times increase patient discomfort while also raising exam costs and limiting scanner th…
GRASP MRI: A Decade of Innovation from Bench to Bedside
Li Feng, Kai Tobias Block, Hersh Chandarana +1
GRASP (Golden-angle RAdial Sparse Parallel) MRI has emerged as one of the most influential motion-robust dynamic MRI frameworks over the past decade. By combining continuous golden…
PSIRNet: Deep Learning-based Free-breathing Rapid Acquisition Late Enhancement Imaging
Arda Atalik, Hui Xue, Rhodri H. Davies +4
Purpose: To develop and evaluate a deep learning (DL) method for free-breathing phase-sensitive inversion recovery (PSIR) late gadolinium enhancement (LGE) cardiac MRI that produce…
Context-aware deep learning using individualized prior information reduces false positives in disease risk prediction and longitudinal health assessment
Lavanya Umapathy, Patricia M Johnson, Tarun Dutt +4
Temporal context in medicine is valuable in assessing key changes in patient health over time. We developed a machine learning framework to integrate diverse context from prior vis…
Multisession Longitudinal Dynamic MRI Incorporating Patient-Specific Prior Image Information Across Time
Jingjia Chen, Hersh Chandarana, Daniel K. Sodickson +1
Serial Magnetic Resonance Imaging (MRI) exams are often performed in clinical practice, offering shared anatomical and motion information across imaging sessions. However, existing…