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

by Gong, Lei , Wang, Lin-Wei , Xu, Jun , Liu, Juan , Liu, Wen-Lou , Li, Yan , Chen, Jia-Mei

in Algorithms / Automation / Biomarkers / Breast cancer / Breast Neoplasms - classification / Breast Neoplasms - diagnostic imaging / Breast Neoplasms - pathology / Digital cameras / Eosine Yellowish-(YS) / Female / Gene expression / Hematoxylin / Histopathology / Humans / Image Interpretation, Computer-Assisted / Image processing / Medical prognosis / Morphology / Pathology / Prognosis / Scanners / Segmentation / Workloads

2017

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

by Gong, Lei , Wang, Lin-Wei , Xu, Jun , Liu, Juan , Liu, Wen-Lou , Li, Yan , Chen, Jia-Mei

2017

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

by Gong, Lei , Wang, Lin-Wei , Xu, Jun , Liu, Juan , Liu, Wen-Lou , Li, Yan , Chen, Jia-Mei

2017

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Journal Article

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

Gong, Lei,

Wang, Lin-Wei,

Xu, Jun,

Liu, Juan,

Liu, Wen-Lou,

Li, Yan,

Chen, Jia-Mei

2017

Overview

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.

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Publisher

SAGE Publications,Sage Publications Ltd,SAGE Publishing

Subject

/ Breast Neoplasms - classification

/ Breast Neoplasms - diagnostic imaging

/ Breast Neoplasms - pathology