Abstract #4863

Synthesizing T2 Maps from Morphological OAI Scans Using Conditional GANs and a Split U-Net

Bragi Sveinsson^1,2,3, Bo Zhu^1,2,3, Akshay Chaudhari⁴, Neha Koonjoo^1,2,3, and Matthew Rosen^1,2,3

¹Martinos Center, Massachusetts General Hospital, Charlestown, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Physics, Harvard University, Cambridge, MA, United States, ⁴Stanford University, Stanford, CA, United States

We explore the feasibility of artificially adding an exam to an MRI scan protocol by synthesizing the desired exam from the acquired images. To achieve this, we both use a normal U-Net as well as a modified U-Net structure, which takes advantage of prior information of which exams of the protocol are most relevant to the high-resolution and low-resolution components of the desired contrast. We demonstrate results based on synthesizing T2 relaxation time maps using imaging data obtained from the Osteoarthritis Initiative.

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