Radial Basis Function Networks and Contrast-Limited Adaptive Histogram Equalization Filter Based Early-Stage Breast Cancer Detection Techniques
- 1 Department of Computational Science and Engineering, Research Scholar, Sathyabama Institute of Science and Technology, Chennai, India
Breast cancer is one of the most common types of cancer that kills women. When cells become uncontrollably large, cancer develops. As a result, detecting and classifying breast cancer in its early stages is essential so that patients can take the appropriate precautions. On the other hand, mammography images have relatively low sensitivity and effectiveness in detecting breast cancer. Furthermore, MRI (Magnetic Resonance Imaging) has higher detection sensitivity for breast cancer than mammography. In this research, a novel Radial Basis Function Networks model (RBFN) with a Mayfly Optimization Algorithm (MAO) mechanism has Breast MRI scans aid in the early detection of breast cancer. Following the system's training on Magnetic Resonance Imaging (MRI) breast images, a unique Contrast-Limited Adaptive Histogram Equalization (CLAHE) filter is developed for pre-processing noisy MRI image material. Backgrounds were removed before recovering breast cancer photos with a Contrast Limited Histogram Equalization (CLAHE) filter. Furthermore, the new study effort's performance is compared to earlier studies and this model is simulated using Python. The proposed model, RBFN-MAO, also outperforms previous models in terms of performance and precision with an accuracy of 97.54%. In comparison, it is 85.28, 80.95, 76.94, 85.39 and 90.32% for Convolution Neural Networks You Only Look Once (CNN-YOLO), Residual Networks (ResNet50), Diffusion Convolution Neural Networks (DCNN), Support Vector Machine (SVM) and Convolution Neural Network (CNN) models, respectively.
Copyright: © 2023 Anitha Ponraj and Aroul Canessane. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Breast Cancer Prediction
- Contrast Limited Histogram Equalization
- Mayfly Optimization Algorithm
- Computer-Aided Diagnosis
- Neural Network
- Deep Learning