Automated Detection and Grading of Non-muscle Invasive Urothelial Cell Carcinoma of the Bladder

May 15, 2020 | Histopathology

First released on The American Journal of Pathology, check out what Lab.Equipment has sourced for your Histopathology industry news fix:

Accurate grading of non-muscle invasive urothelial cell carcinoma (UCC) is of major importance, however high inter-observer variability exists. A fully-automated detection and grading network based on deep learning is proposed to enhance reproducibility. A total of 328 transurethral resection specimens from 232 patients were included. A consensus reading by three specialized pathologists was utilized. The slides were digitized and the urothelium was annotated by expert observers. The U-Net based segmentation network was trained to automatically detect urothelium in the sections... Read the full article at The American Journal of Pathology Blog.

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