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Breast Cancer Histopathology Image Analysis: A Review

IEEE Transactions on Biomedical Engineering · 2014 · Vol. 61(5) · pp. 1400–1411
Mitko VetaJosien P. W. PluimP. J. van DiestMax A. Viergever

Abstract

This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

AI in cancer detectionCell Image Analysis TechniquesRadiomics and Machine Learning in Medical ImagingHistopathologyBreast cancerDigital pathologyDigitizationPathologyComputer scienceCancerMedical physicsMedicineComputer vision

MeSH terms

Breast NeoplasmsFemaleHistocytochemistryHumansImage Interpretation, Computer-AssistedMicroscopy
Citations
691
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50.92
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Cited by
A Dataset for Breast Cancer Histopathological Image Classification
IEEE Transactions on Biomedical Engineering · 2015 · 1,694 citations
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