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arXiv · 1805.05392

An Automatic Patch-based Approach for HER-2 Scoring in Immunohistochemical Breast Cancer Images Using Color Features

Caroline Q. Cordeiro·Sergio O. Ioshii·Jeovane H. Alves·Lucas F. Oliveira
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Abstract

Breast cancer (BC) is the most common cancer among women world-wide, approximately 20-25% of BCs are HER-2 positive. Analysis of HER-2 is fundamental to defining the appropriate therapy for patients with breast cancer. Inter-pathologist variability in the test results can affect diagnostic accuracy. The present study intends to propose an automatic scoring HER-2 algorithm. Based on color features, the technique is fully-automated and avoids segmentation, showing a concordance higher than 90% with a pathologist in the experiments realized.

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Caroline Q. Cordeiro, Sergio O. Ioshii, Jeovane H. Alves, Lucas F. Oliveira. 2018-05-14. An Automatic Patch-based Approach for HER-2 Scoring in Immunohistochemical Breast Cancer Images Using Color Features. https://arxiv.org/abs/1805.05392

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