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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM31181
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Breast cancer is one of the most common malignant tumors in women, which seriously affect women’s physical and mental health and even threat to life. At present, microscopic images are the important criterion for doctors to diagnose breast cancer. However, due to the complex structure of microscopic images, it is relatively difficult for doctors to identify breast cancer features. Deep learning is the most mainstream image classification algorithm which uses Convolutional Neural Network (CNN). In this project first, the BreakHis400x (Breast Cancer Histopathological Images) images will undergo pre-processing such as enhancement and data augmentation in order to increase the number of images. Secondly, the pre-processed dataset will be trained on deep learning model that extracts the features and generate the performance evaluation metric of CNN models. We are going to use python software for classifying the images.
KEYWORDS
Publication Date
12/31/45401
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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