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Abstract #3549

Predicting T2 Maps from Morphological OAI Images with an ROI-Focused GAN

Bragi Sveinsson1,2, Akshay Chaudhari3, Bo Zhu1,2, Neha Koonjoo1,2, and Matthew Rosen1,2
1Massachusetts General Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Stanford University, Stanford, CA, United States

The osteoarthritis initiative (OAI) performed several morphological MRI scans on both knees of a large patient cohort, but only acquired T2 maps in the right knee of most patients. We train a conditional GAN to use the morphological scans acquired in both knees to predict the T2 map, using the acquired T2 map in the right knee as a training target. Post-training, we apply the network to predict T2 values in the left knee, without an acquired T2 map.

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