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Decoding the visual attention of pathologists to reveal their level of expertise
March 27, 2024, 4:46 a.m. | Souradeep Chakraborty, Dana Perez, Paul Friedman, Natallia Sheuka, Constantin Friedman, Oksana Yaskiv, Rajarsi Gupta, Gregory J. Zelinsky, Joel H. Sal
cs.CV updates on arXiv.org arxiv.org
Abstract: We present a method for classifying the expertise of a pathologist based on how they allocated their attention during a cancer reading. We engage this decoding task by developing a novel method for predicting the attention of pathologists as they read whole-slide Images (WSIs) of prostate and make cancer grade classifications. Our ground truth measure of a pathologists' attention is the x, y and z (magnification) movement of their viewport as they navigated through WSIs …
abstract arxiv attention cancer cs.cv decoding eess.iv expertise images novel reading type visual visual attention
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