Publication | Closed Access
GLCM Textural Features for Brain Tumor Classification
248
Citations
7
References
2012
Year
Unknown Venue
EngineeringDigital PathologyRecognition SystemGliomaDiagnostic ImagingNeuro-oncologyImage AnalysisPattern RecognitionBrain TumorNeurologyGlcm Textural FeaturesRadiologyMedical ImagingNeuroimagingDeep LearningMedical Image ComputingRadiomicsMedical ImagesBiomedical ImagingComputer-aided DiagnosisNeuroscienceTexture AnalysisMedicineMedical Image Analysis
Automatic recognition system for medical images is challenging task in the field of medical image processing. Medical images acquired from different modalities such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), etc which are used for the diagnosis purpose. In the medical field, brain tumor classification is very important phase for the further treatment. Human interpretation of large number of MRI slices (Normal or Abnormal) may leads to misclassification hence there is need of such a automated recognition system, which can classify the type of the brain tumor. In this research work, we used four different classes of brain tumors and extracted the GLCM based textural features of each class, and applied to twolayered Feed forward Neural Network, which gives 97.5% classification rate.
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