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

arXiv: https://arxiv.org/abs/1805.05392 · HTML: https://mlsanity.com/paper/1805.05392/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 May 2018.

## Built on by (most cited first, 1 of 1)

- [convoHER2: A Deep Neural Network for Multi-Stage Classification of HER2 Breast Cancer](https://mlsanity.com/paper/2211.10690/) (2022)

## Abstract (arXiv)

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.