Detection and Classification of Brain Tumor using Support Vector Machine Based GUI
- Resource Type
- Conference
- Authors
- Khan, Imran Ullah; Akhter, Shamim; Khan, Shaheen
- Source
- 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN) Signal Processing and Integrated Networks (SPIN), 2020 7th International Conference on. :739-744 Feb, 2020
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Feature extraction
Support vector machines
Tumors
Graphical user interfaces
Cancer
Training
Matlab
Support vector machine
GUI
- Language
- ISSN
- 2688-769X
Medical image segmentation is a challenging task in the field of medical science. Many tools have been developed by engineers to detect tumor and perform analysis of medical images. The most important and effective role in the entire procedure is played by image segmentation tool. It has attracted a lot of attention in the last so many years and researchers are continuously working to increase its quality and attributes. This paper is about the detection of brain tumor using a support vector machine based interface using GUI in Matlab. The interface can use any combination of segmentation, filtering and other techniques to achieve optimum results. The algorithm begins with noise removal and feature extraction using discrete wavelet transform. The extracted features include both first and second order features. These features are reduced to the desired level using principle component analysis. These features are also used to train the kernel SVM. The classification is then performed by support vector machine. The interface of GUI is developed using Matlab guide.