GAN GAO

Ph.D. student @UW

[GAN GAO @gaogan96]

Huge thanks to @GreatAndrew90 for his tremendous support, Professors @jonliu123 and @AI4Pathology for their insightful guidance, and everyone else who contributed to this work!

[GAN GAO @gaogan96]

Our paper is out @CVPR CVMI workshop!
https://t.co/FwdPAnQvPh

We report a DL approach that leverages contextual information along the depth axis to identify the highest-risk 2D sections within whole biopsies to help pathologists diagnose diseases more accurately.