MSBI Program Research Projects
UCSF’s Department of Radiology and Biomedical Imaging consistently ranks amongst the top departments in the nation in terms of funding from the National Institutes of Health. There is a wide breadth of research performed, ranging from basic science to applied clinical research. MSBI students are free to engage in imaging based research in other departments, which have included Cardiology, Neurology, Ophthalmology and Dentistry. Alternatively, students can engage in an internship at one of the bay area’s biotechnology or pharmaceutical companies.
The MSBI program encourages students to explore their own research interests and many research opportunities exist within the Department of Radiology and Biomedical Imaging, in other departments at UCSF, and even in local biotechnology and pharmaceutical companies. A research elective course is introduced in the Spring quarter, which allows students time to explore potential research topics. Most MSBI students pursue the thesis option, which allows them to spend the summer quarter working full time on their research project. The vast majority of MSBI thesis students receive a stipend during the summer quarter. Summaries of the range of projects undertaken by MSBI students can be found at the links below.
Thesis & Abstracts
2019 - 2020
| Casey Alcantar | A Faster R-CNN Model for Detection of MR-Compatible Catheters |
| Souradeep Gogol Bhattacharya | An imaging informatics-based risk assessment for early detection of depressive symptom onset |
| Jacob Ellison | Improving the generalizability of convolutional neural networks for brain tumor segmentation in the post-treatment setting |
| Anil Kemisetti | |
| Chieh Te Jack Lin | Synthesis of DFO with PSMA-targeted inhibitor labeled 89Zr to evaluate prostate cancer |
| Jacob Oeding | Automatic Three-Dimensional Bone Shape Modeling Using Clinical MRI |
| Jonathan Renslo | Distinguishing porosity and vasculature changes in Type 2 Diabetes (T2D) in distal tibia with MRI and HRqCT |
| Avantika Sinha | Software Improvements for Processing and Analysis of Hyperpolarized MRI Data |
| Bishal Upadhyaya | A Comparison of FDG and Amyloid PET for the Deep Learning Prediction of Alzheimer’s Disease in Low Income Communities |
2018 - 2019
| Ravi Chachad | Temporal Impact of Sugar Metabolism on the Liver |
| Qing Dai | Clear Cell Renal Cell Carcinoma: Deep Learning-Based Prediction of Tumor Grade from Contrast-Enhanced CT |
| Emilie Decavel-Bueff | Drug capture efficacy using polystyrenesulfonate-coated chemofilter device |
| Virginia Hinostroza | 4D Flow with Compressed Sensing for the Evaluation of Intracranial Aneurysmal Flow |
| Alison Myoraku | Lifespan Changes of the Human Insula in Major Depression |
| Samuel Shu | Understanding differences in quantification of conventional versus experimental contrast materials with different clinical dual-energy computed tomography systems, and development of universal contrast quantification “handshake” |
| Benjamin Sipes | EEG Microstates in Neurofeedback Attention Training |
| Torie Tsuie | Longitudinal Changes in Brain Structure and Integrity During Acute HIV |
| Jack Williams | Evaluating EPflex MRline Guidewire for Endovascular Interventions Guided by MRI at 3T vs. X-ray Fluoroscopy |
| Fei Xiong | Prediction of Abdominal Aortic Aneurysms (AAAs) Progression by Automatic Segmentation and Radiomics Feature Quantification |
| Jiamin Zhou | spectrome-AI: a Neural Network Framework for Inferring MEG Spectra |