Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review

Author:

Chen Jia-Mei1,Li Yan12,Xu Jun3,Gong Lei3,Wang Lin-Wei1,Liu Wen-Lou1,Liu Juan4

Affiliation:

1. Department of Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors & Hubei Cancer Clinical Study Center, Wuhan, China

2. Department of Peritoneal Cancer Surgery, Beijing Shijitan Hospital of Capital Medical University, Beijing, China

3. Jiangsu Key Laboratory of Big Data Analysis Technique, Nanjing University of Information Science and Technology, Nanjing, China

4. State Key Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan, China

Abstract

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature–based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

Publisher

IOS Press

Subject

General Medicine

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