Automatic Ischemic Stroke Segmentation Using Various Techniques
Different methods of automatic segmentation of human brain ischemic stroke area in the computerized tomography scans are compared. Experts-radiologists performed the evaluation of segmentation techniques. A methodology of qualitative evaluation of the investigated methods is proposed. The best viability showed histogram, gray level co-occurrence matrix, mean and standard deviation methods, and supervised artificial neural network technique.
KeywordsIschemic Stroke Artificial Neural Network Image Segmentation Gray Level Medical Image Analysis
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