International Journal of Bioscience Biochemistry and Bioinformatics · 2017 · 10 citations · 2 references
MedicineBioengineeringBiomedical EngineeringBiomedical ImagingComputer VisionDiagnostic ImagingBrain TumorsCancer DetectionImage AnalysisImage SegmentationMedical ImagingTumor DetectionClusteringContrast EnhancementDicomGaussian FiltersK-means ClusteringMedical Image SegmentationSegmentationTumor Segmentation
The aim of this paper is to propose a matlab toolbox of a comparative study of four brain tumor segmentation methods with specific sequences. Four methods are K-means clustering, fuzzy C-means clustering, Region growing, and Otsu segmentation. Skull stripping algorithm has done before segmentation. Different preprocessing algorithms are applied before segmentation to enhance images and give better segmentation. Median filter, Gaussian filter, and contrast enhancement are applied according to segmentation method. The database used is based on DICOM images. GLCM used for feature extraction. Classification and accuracy measurement are done by ANN.
2