Mitotic Cell Detection in Breast Histopathology Image: A Review

Abstract

Mitotic assessment is one of the critical features in the Nottingham Histological Grading (NHG) system for breast cancer grading. In recent years, rapid development in the performance of mounted camera, computer processing power, and data processing speed have fostered the research interest in detection of mitotic cells using image processing techniques. This paper is meant as an introduction of the recent methods and approaches specifically in detection of mitotic cells for the non-experts. It starts with overview of the grading system, online dataset, and the recent proposed methods in each step (i.e., color normalization, nuclei detection, feature extraction, and classification) of the mitotic cell assessment procedure. A brief discussion and the open problems pertinent to the established works were presented at the end of this paper.

A Systematic Approach to Identify the Breast Cancer Grades in Histopathological Images Using Deep Neural Networks

“…Some of the previous works related to the objectives are defined here. Jian et al mainly applied several classification techniques to distinguish mitotic cells from healthy normal cells [7]. S. Rao has introduced a method involving a region-based convolutional neural network to identify the mitotic elements in histopathological images [8].…”