International Conference on Artificial Intelligence · 2010 · 72 citations · 11 references
ComputingComputer ScienceOncologyComputer VisionDiagnostic ImagingNeuro-oncologyBrain TumorsImage AnalysisImage SegmentationMedical Image AnalysisTexture AnalysisTumor ClassificationBrain Tumor DiagnosisFeature Extraction For SegmentationLesion ClassificationMedical Image SegmentationSegmentation By TextureTexture Feature ExtractionTexture-based SegmentationTumor Segmentation
Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way for diagnosis of the brain tumor. Proposed system consists of multiple phases. First phase consists of texture feature extraction from brain MR images. Second phase classify brain images on the bases of these texture feature using ensemble base classifier. After classification tumor region is extracted from those images which are classified as malignant using two-stage segmentation process. Segmentation consists of skull removal and tumor extraction phases. Quantitative results show that our proposed system performed very efficiently and accurately. We achieved accuracy of classification beyond 99%. Segmentation results also show that brain tumor region is extracted quite accurately.
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