Classification of breast cancer based on histological images using CNN

Saurabh Waikule; Prachi Shingvi; Shashank Thigale; M. R. Mahajan

Classification of breast cancer based on histological images using CNN

Authors: Saurabh Waikule, Prachi Shingvi, Shashank Thigale, M. R. Mahajan

Unique Paper ID: 148149
Volume: 5
Issue: 12
PageNo: 604-608

Keywords: Breast cancer Classification Convolutional Neural Network (CNN) Deep learning Histopathological image.

Abstract:
Breast cancer is one of the most significant reasons for death among women. Early diagnosis significantly increase the chance of correct treatment and survival but this process is tedious and often leads to disagreement between pathologists. Computer based analysis showed potential for improving diagnostics accuracy. Many research has been done on the detection and classification of breast cancer using various image processing and classification techniques. The performance of most conventional classification system relies on feature extraction and appropriate data representation. On the other hand deep learning can organize discriminative information from data. Using CNN we propose a method for classification of histology images into benign and malignant and also subclasses. For 2 class classification task, we report 88% accuracy and for 4 class classification task, we report 85% to 89% accuracy.

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ISSN: 2349-6002
Volume: 5
Issue: 12
PageNo: 604-608

Classification of breast cancer based on histological images using CNN

Available:https://ijirt.org/Article?manuscript=148149

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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