2 citations · 2 across the 4 of their papers we have counts for
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Improved Robustness for Deep Learning-based Segmentation of Multi-Center Myocardial Perfusion MRI Datasets Using Data Adaptive Uncertainty-guided Space-time Analysis
Dilek M. Yalcinkaya, Khalid Youssef, Bobak Heydari +8
Background. Fully automatic analysis of myocardial perfusion MRI datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart dis…
Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction
Yuning Du, Yuyang Xue, Rohan Dharmakumar +1
Deep learning (DL) reconstruction particularly of MRI has led to improvements in image fidelity and reduction of acquisition time. In neuroimaging, DL methods can reconstruct high-…
Temporal Uncertainty Localization to Enable Human-in-the-loop Analysis of Dynamic Contrast-enhanced Cardiac MRI Datasets
Dilek M. Yalcinkaya, Khalid Youssef, Bobak Heydari +4
Dynamic contrast-enhanced (DCE) cardiac magnetic resonance imaging (CMRI) is a widely used modality for diagnosing myocardial blood flow (perfusion) abnormalities. During a typical…