Abstract #1619

Developments of Unet, Unet plus Conditional Random Field Insert, and Bayesian Vnet CNNs for Zonal Prostate Segmentation

Peng Cao¹, Susan Noworolski¹, Sage Kramer¹, Valentina Pedoia¹, Antonio Westphalen¹, and Peder Larson¹

¹Department of Radiology, University of California at San Francisco, San Francisco, CA, United States

We studied 2d and 3d fully convolutional neural network for zonal prostate segmentation from T2 weighted MRI data. We also introduce a new methodology that combines Unet and conditional random field insert (CRFI) to improve the accuracy and robustness of the segmentation.

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