What is it about?
Breast cancer is considered as one of the most perilous sickness among females worldwide and the ratio of new cases is increasing yearly. Many researchers have proposed efficient algorithms to diagnose breast cancer at early stages, which have increased the efficiency and performance by utilizing the learned features of gold standard histopathological images.
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Why is it important?
Breast cancer is considered as one of the most perilous sickness among females worldwide and the ratio of new cases is increasing yearly.
Perspectives
The method concentrates on histopathological images to classify the breast cancer. The performance is compared with the state-of-the-art techniques, where an overall patient-level accuracy of 97.2% and image-level accuracy of 96.7% is recorded.
Inzamam Mashood Nasir
HITEC University
Read the Original
This page is a summary of: An Optimized Approach for Breast Cancer Classification for Histopathological Images Based on Hybrid Feature Set, Current Medical Imaging Formerly Current Medical Imaging Reviews, March 2021, Bentham Science Publishers,
DOI: 10.2174/1573405616666200423085826.
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