Case Study: U-Net TensorFlow with INS, Rapperswil¶
In collaboration with the Institute for Networked Solutions INS we used XamFlow and TensorFlow U-Net to automate prostate segmentation.
Prostate MR images from MRI T2 acquisitions
5251 slices of 181 patients
Captures with various machines using multiple protocols
Preprocessed to normalize all the data
Augmented using various methods
Martin Stypinski, ProSeg – Increasing Robustness in ProstateSegmentation with Deep Learning, Master Thesis