A Clinical Support System for Brain Tumor Classification Using Soft Computing Techniques

A brain tumor is an accumulation of abnormal cells in human brain. As tumor increases in size, it induces brain damage. Hence it is essential to diagnose the type of brain tumor. The effective modality used for brain tumor diagnose is MRI because of its remarkable image resolution, the speed of acqu...

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Bibliographic Details
Published in:Journal of medical systems 2019-05, Vol.43 (5), p.144-11, Article 144
Main Authors: Arasi, P. Rupa Ezhil, Suganthi, M.
Format: Article
Language:English
Subjects:
Algorithms
Brain - pathology
Brain cancer
Brain damage
Brain injury
Brain Neoplasms - diagnosis
Brain Neoplasms - diagnostic imaging
Brain Neoplasms - pathology
Brain tumors
Classification
Clustering
Decision Support Systems, Clinical
Feature extraction
Fuzzy Logic
Health Informatics
Health Sciences
Humans
Image & Signal Processing
Image acquisition
Image classification
Image processing
Image Processing, Computer-Assisted - methods
Image resolution
Image segmentation
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Medical imaging
Medical personnel
Medicine
Medicine & Public Health
Neuroimaging
Soft computing
Statistics for Life Sciences
Support systems
Support Vector Machine
Support vector machines
Tumors
Wearable Computing Techniques for Smart Health
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Description
Summary:A brain tumor is an accumulation of abnormal cells in human brain. As tumor increases in size, it induces brain damage. Hence it is essential to diagnose the type of brain tumor. The effective modality used for brain tumor diagnose is MRI because of its remarkable image resolution, the speed of acquisition, and high safety profile for patients. The analysis of brain MRI is an important part of patient care and decision. Hence in the proposed Clinical Support System, the brain MRI image is preprocessed using Genetic Optimized Median Filter followed by brain tumor region segmentation using Hierarchical Fuzzy Clustering Algorithm. The features of the tumor region are extracted through GLCM feature extraction method. Lion Optimized Boosting Support Vector machine model is used for further classification of tumor by Brain Tumor Image Segmentation (BraTS) dataset. Hence the proposed clinical support system provides an integrated model for Detection and classification of brain tumor which assists the doctors in appropriate evaluation of tumor.
ISSN:0148-5598
1573-689X
DOI:10.1007/s10916-019-1266-9