| 1-R21-EB034911-01A1 |
Deep Learning for Individualized Treatment Effect Inference with Multimodal Depiction |
Xiaofeng Liu |
Yale University |
| 5-R01-EB031806-04 |
Deep Learning Reconstruction for Improved TOF PET Using Histo-Image Partitioning |
Samuel Matej |
University of Pennsylvania |
| 5-R21-EB031185-03 |
Deep Learning Reconstruction for Rapid Multi-Component Relaxometry |
Fang Liu |
Massachusetts General Hospital |
| 1-R01-EB034249-01 |
Deep learning technologies for estimating the optimal task performance of medical imaging systems |
Mark Anastasio |
University of Illinois at Urbana-Champaign |
| 5-R21-EB032597-02 |
Deep Learning To Automate Late Mechanical Activation Detection From Cardiac Magnetic Resonance Images |
Miaomiao Zhang |
University of Virginia |
| 5-R03-EB032793-02 |
Deep Learning-Enabled Arterial Pulse Waveform Analysis Approach to Peripheral Artery Disease Diagnosis |
Jin-Oh Hahn |
Univ of Maryland, College Park |
| 2-R56-EB004640-16 |
Deep LOGISMOS |
Milan Sonka |
University of Iowa |
| 5-R21-EB029493-03 |
Development of quantitative tools to predict patients with difficult intubation to minimize treatment related complications |
Muhammad Khalid Khan Niazi |
Wake Forest University Health Sciences |
| 2-R01-EB017095-10 |
Diagnostic performance assessment and dose optimization using patient CT images: Application to deep-learning CT reconstruction and denoising technologies |
Cynthia Mccollough |
Mayo Clinic Rochester |
| 1-R21-EB033426-01A1 |
DL-based CT image formation with characterization and control of resolution and noise |
Jingyan Xu |
Johns Hopkins University |
