Multi-Deep CNN based Experimentations for Early Diagnosis of Breast Cancer
Author:
Affiliation:
1. Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam 638401, India
2. Department of Computer Science and Engineering, Dayananda Sagar University, Bangalore, India
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science
Link
https://www.tandfonline.com/doi/pdf/10.1080/03772063.2022.2028584
Reference54 articles.
1. Sliding Window Based Support Vector Machine System for Classification of Breast Cancer Using Histopathological Microscopic Images
2. Automated Computer Aided Diagnosis Using Altered Multi-Phase Level Sets in Application to Categorize the Breast Cancer Biopsy Images
3. Performance analysis and detection of micro calcification in digital mammograms using wavelet features
4. A comparison of detrend fluctuation analysis, Gaussian mixture model and artificial neural network performance in the detection of microcalcification from digital mammograms
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