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Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs
March 13, 2024, 4:43 a.m. | Neel Kanwal, Farbod Khoraminia, Umay Kiraz, Andres Mosquera-Zamudio, Carlos Monteagudo, Emiel A. M. Janssen, Tahlita C. M. Zuiverloon, Chunmig Rong, K
cs.LG updates on arXiv.org arxiv.org
Abstract: Histopathology is a gold standard for cancer diagnosis under a microscopic examination. However, histological tissue processing procedures result in artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs). Artifacts are diagnostically irrelevant areas and may result in wrong deep learning (DL) algorithms predictions. Therefore, detecting and excluding artifacts in the computational pathology (CPATH) system is essential for reliable automated diagnosis. In this paper, we propose a …
abstract artifact arxiv cancer cancer diagnosis computation computational cs.ai cs.cv cs.lg diagnosis eess.iv glass however images pathology performance pipelines processing slides standard systems trade type
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