Breast Cancer Detection using Support Vector Machine (SVM) Test phase, srs, design phase and source code final deliverable
Project Domain /
Category
Image Processing
Abstract /
Introduction
Early detection of breast cancer ensures the chances of survival. Now a days the best technique is mammography which uses x-rays to detect breast cancer at initial stages. The main objective of this project is to enhance the accuracy of the cancer detection and classify the women into different risks groups on the basis of physiological symptoms. X-rays images are used as input to Support Vector Machine (SVM) classifier. The steps involved in the cancer detection using x-rays are represented graphically:
Steps to perform classification
Functional Requirements:
Provide a bulleted list of functional requirements
- Input x-rays images by creating web page.
- Perform pre-processing to reduce anomalies and noisy data.
- Apply segmentation.
- Feature extraction using Gaussian function.
- Classify data into different risk groups on the basis of symptoms.
- Show results graphically and statistically.
Tools:
You can use any tool related to the project like MATLAB, Weka, C#, Java Python
Note: dataset will be provided later.