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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Publicado en:Journal of Medical Systems Vol. 43; no. 5
Autores principales: Arasi, P. Rupa Ezhil, Suganthi, M.
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature May2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2019
      vid: 43
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      pub: Springer Nature
      place: New York, New York
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        atl: A Clinical Support System for Brain Tumor Classification Using Soft Computing Techniques.
      aug:
        au:
          Arasi, P. Rupa Ezhil
          Suganthi, M.
        affil: Department of Computer Science and Engineering, Muthayammal Engineering College, Rasipuram, Namakkal (Dt), 637 408, Tamilnadu, India
      sug:
        subj:
          Brain Neoplasms Classification
          Magnetic Resonance Imaging Equipment and Supplies
          Image Processing, Computer Assisted Methods
          Computing Methodologies
          Decision Support Systems, Clinical
          Human
          Algorithms
          Software
          Models, Statistical
          Brain Neoplasms Radiography
          Brain Neoplasms Pathology
          Tumor Burden Evaluation
          Neoplasm Staging
          Physicians Education
      ab: 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.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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