Classification of breast cancer based on histological images using CNN
Author(s):
Saurabh Waikule, Prachi Shingvi, Shashank Thigale, M. R. Mahajan
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.
Article Details
Unique Paper ID: 148149

Publication Volume & Issue: Volume 5, Issue 12

Page(s): 604 - 608
Article Preview & Download




Go To Issue



Call For Paper

Volume 6 Issue 4

Last Date 25 September 2019


About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:8200 61 5067
Email: editor@ijirt.org
Website: ijirt.org

Policies