2. What was your primary T32 research project?
KM: My project was to develop and validate deep learning tools to predict clinically significant prostate cancer from prostate MRI using a variety of imaging inputs − prostate MRI sequences (T2WI, ADC, DWI) and PSMA PET − as well as pathology ground truths − MR/ultrasound (US) combined fusion biopsy, systematic biopsy and whole mount prostatectomy.
TG: My primary research project involves the use of artificial intelligence (AI) derived segmentation algorithms to detect changes in low-grade glioma tumor volumes over time.
3. How do you think the T32 program benefitted your career in academic radiology?
KM: The dedicated time that the T32 program offered me along with the mentorship of UCSF Radiology faculty was invaluable.
TG: The T32 program gave me the opportunity to get deeply involved in research projects while…
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