Breast Cancer Detection Using Extreme Learning machine Based on Feature Fusion with CNN Deep Features
Product Description
Aim:
To classify benign and malignant breast masses using K Nearest Neighbor based on Feature Fusion with CNN Deep Features.
Synopsis:
A computer-aided diagnosis (CAD) system based on mammograms enables early breast Cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD systems remains unsatisfactory. This project explores a breast CAD method based on feature fusion with Convolution neural network (CNN) deep features.
Proposed system:
We propose a mass detection method based on CNN deep features and unsupervised K Nearest Neighbor (KNN) clustering. Second, we build a feature set fusing deep features, morphological features, texture features, and density features. Third, an KNN classifier is developed using the fused feature set to classify benign and malignant breast masses. Extensive experiments demonstrate the accuracy and efficiency of our proposed mass detection and breast cancer classification method.
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Package Includes
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- Demo Video
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The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days
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- Demo Video
- Abstract
- Base paper
- Full Project PPT
- Datasheets
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- Screen Shots & Photos
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- Reference Papers
- Lit survey
- Full Project Documentation
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The Delivery time for Hardware
projects is 7-8 working days.
Mini Projects: Software Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- UML Diagrams
- SRS
- Source Code
- Screen Shots
- Software Links
- Reference Papers
- Full Project Documentation
- Online support
The
Delivery time for software Miniprojects is 2 -3 working days.
Mini Projects - Hardware includes
- Demo Video
- Abstract
- PPT
- Datasheets
- Circuit Diagrams
- Source Code
- Screen Shots & Photos
- Software Links
- Reference Papers
- Full Project Documentation
- Online
support
The Delivery time for Hardware Mini projects is 7-8 working days.