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Taxonomy: IM- MRI : Quantitative Imaging
| PO-GePV-I-8 | Fast T1 Mapping Optimization: A Phantom Study Z Razi1*, Z Zhang2, Z Mullaghy1, A Lloyd3, H Liu1, M Arreola1, (1) University of Florida, Gainesville, FL, (2) Washington University School of Medicine, Saint Louis, MO (3) University of Florida Health, Gainesville, FL |
| PO-GePV-I-9 | Commissioning of Commercial Quantitative R2* Mapping Software for Clinical Use B Taylor*, H Chen, H Liu, J Yung, P Hou, K Brock, RJ Stafford, Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX |
| TH-C-TRACK 3-5 | Novel Sampling Strategy for Improved Reproducibility in Quantitative T1rho Mapping C Wu1*, Q Peng2, (1) Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA (2) Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA |
| TH-IePD-TRACK 2-3 | Leveraging Prior Knowledge to Reconstruct Quantitative MR Relaxation Maps to Investigate Glioma Tumor Heterogeneity X Zhao1*, D Parsons2, Z Iqbal1, (1) University of Alabama - Birmingham, Birmingham, AL, (2) UT Southwestern Medical Center, Dallas, TX |
| TH-IePD-TRACK 2-5 | Deep Learning Based T2* Mapping From MRI Images with Different Types of Weighting Y Wu1, Y Ma2, N Kovalchuk1, J Du2, L Xing1*, (1) Stanford University, Palo Alto, CA, (2) University of California San Diego, San Diego, CA |
| TH-IePD-TRACK 2-6 | Quantitative Inter-Vendor Evaluation of PDFF and R2* Mapping Accuracy for 3T MRI Scanners J Yu*, A Panda, Mayo Clinic, Arizona, Scottsdale, AZ |