| Deep Learning-Based Segmentation and Uncertainty Assessment for Automated Analysis of Myocardial Perfusion MRI Datasets Using Patch-Level Training and Advanced Data Augmentation DM Yalcinkaya, K Youssef, B Heydari, L Zamudio, R Dharmakumar, ... 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 6 | 2021 |
| Clinician-in-the-loop Analysis of FBee-breathing Stress Perfusion CMR Datasets with Dynamic Quality Control: Preliminary Evaluation Using the SCMR Registry DM Yalcinkaya, K Youssef, Z Li, B Heydari, R Dharmakumar, R Judd, ... Journal of Cardiovascular Magnetic Resonance 26, 2024 | 1 | 2024 |
| Automatic Segmentation of Multi-center Multi-field-strength Perfusion CMR Datasets with Deep Learning-based Uncertainty-guided Analysis: Preliminary Findings Using the SCMR … DM Yalcinkaya, Z Li, K Youssef, LZ Rivero, V Polsani, M Elliott, ... Journal of Cardiovascular Magnetic Resonance 26, 2024 | 1 | 2024 |
| Temporal Uncertainty Localization to Enable Human-in-the-loop Analysis of Dynamic Contrast-enhanced Cardiac MRI Datasets DM Yalcinkaya, K Youssef, B Heydari, O Simonetti, R Dharmakumar, ... International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 1 | 2023 |
| Improved robustness for deep learning-based segmentation of multi-center myocardial perfusion cardiovascular MRI datasets using data-adaptive uncertainty–guided space-time analysis DM Yalcinkaya, K Youssef, B Heydari, J Wei, CNB Merz, R Judd, ... Journal of Cardiovascular Magnetic Resonance 26 (2), 101082, 2024 | | 2024 |
| Retrospective Phase-map Synthesis for CMR Datasets FBom Magnitude-only DICOM Images Enabled by AI Generative Models to Create Large Training Datasets for Deep Learning-based … MB Sahin, DM Yalcinkaya, R Dharmakumar, A Hashemi, B Sharif Journal of Cardiovascular Magnetic Resonance 26, 2024 | | 2024 |
| Improved Robustness for Deep Learning-based Segmentation of Perfusion CMR Datasets Using Data Adaptive Uncertainty-guided Spatiotemporal Analysis DM Yalcinkaya, K Youssef, B Heydari, S Raman, R Dharmakumar, ... Proc of the 26th Annual Scientific Sessions of SCMR, 2023 | | 2023 |
| Uncertainty Assessment for Deep Learning-based Segmentation of Stress Perfusion CMR Using Patch-Level Training and Test-time Analysis DM Yalcinkaya, K Youssef, B Heydari, L Zamudio, R Dharmakumar, ... Proc of the 25th Annual Scientific Sessions of SCMR, 2022 | | 2022 |
| Deep Learning-based Segmentation of Myocardial Perfusion CMR: The Role of Patch-based Training and Advanced Data Augmentation DM Yalcinkaya, K Youssef, T Beaulieu, H Unal, R Dharmakumar, B Sharif Proc of the 24th Annual Scientific Sessions of SCMR, 2021 | | 2021 |
| Retrospective k-Space Synthesis for Cardiac MRI Deep-learning Applications from Magnitude-only Images Using Score-based Diffusion Models DM Yalcinkaya, MB Sahin, R Dharmakumar, A Hashemi, B Sharif | | |
| Efficient Analysis of Myocardial Perfusion MRI with Human-in-the-loop Dynamic Quality Control: Initial Results Using the SCMR Registry DM Yalcinkaya, Z Li, K Youssef, B Heydari, R Dharmakumar, R Judd, ... | | |
| Improved Robustness for Deep Learning-based Segmentation of Perfusion CMR Using Data Adaptive Uncertainty-guided Spatiotemporal Analysis DM Yalcinkaya, K Youssef, B Heydari, S Raman, R Dharmakumar, ... | | |
| Data-adapted Neural Network Denoisers as a Regularization Engine for Low-latency Image Reconstruction in Accelerated Cardiac Perfusion MRI DM Yalcinkaya, HB Unal, S Raman, A Hashemi, R Dharmakumar, ... | | |
