This is a brief collection of work that I have been working on since entering MSK May 2019.
Papers/Abstracts: The following abstracts were accepted for persentations for conferences of the International Society for Magnetic Resonance in Medicine.
- "Personalized DCE-MRI parametric mapping of gynecological cancer using high spatiotemporal resolution GRASP" Kim N, ... , Otazo R. ISMRM 2020 Annual Conference and Exhibition.
- "Motion-resistant XDGRASP for free-breathing liver MRI: qualitative comparison with standard breath-hold hepatobiliary phase imaging" Kim N, ... , Otazo R. ISMRM 2020 Annual Conference and Exhibition
- "MR SIGnature MAtching (MRSIGMA) with motion baseline drift adaptation for real-time volumetric motion tracking" Kim N,..., Otazo R. ISMRM 2020 Image Reconstruction and Data Sampling workshop.
Code Snippets:
- KTSS: A project focused on learning the basics of MR Imaging. Without looking at already published code, I recreated the k-t sparse sense reconstruction algorithm using Python.
- Deep Learning Reconstruction: A collection of sample code that has been developed in pursuing a deep learning reconstruction algorithm for MR Imaging. We are working on using Deep Learning to speed up reconstruction of Magnetic Resonance images. Currently are focusing on fixing the issues of "hallucinations" that occur when using deep learning by incorporating data consistency.