title: Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review.
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.
authors.affiliation: 1 Department of Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors & Hubei Cancer Clinical Study Center, Wuhan, China.
authors.forename: Jia-Mei
authors.initials: JM
authors.lastname: Chen
authors.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.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.affiliation: 3 Jiangsu Key Laboratory of Big Data Analysis Technique, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Xu
authors.affiliation: 3 Jiangsu Key Laboratory of Big Data Analysis Technique, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Lei
authors.initials: L
authors.lastname: Gong
authors.affiliation: 1 Department of Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors & Hubei Cancer Clinical Study Center, Wuhan, China.
authors.forename: Lin-Wei
authors.initials: LW
authors.lastname: Wang
authors.affiliation: 1 Department of Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors & Hubei Cancer Clinical Study Center, Wuhan, China.
authors.forename: Wen-Lou
authors.initials: WL
authors.lastname: Liu
authors.affiliation: 4 State Key Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan, China.
authors.forename: Juan
authors.initials: J
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000000981:diagnostic imaging* / Q000473:pathology; D004801:Eosine Yellowish-(YS); D005260:Female; D006416:Hematoxylin; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D011379:Prognosis
chemical_list: D004801:Eosine Yellowish-(YS); D006416:Hematoxylin
keywords: Breast cancer; computer-aided prognosis; hematoxylin and eosin histopathology image; image analysis