Detection and Segmentation of Hemorrhage Stroke using Textural Analysis on Brain CT Images
Alyaa Hussein Ali1, Shahad Imad Abdulsalam2, Ihssan Subhi Nema3
1Dr. Alyaa Hussein Ali, Assistant professor, in Department of Physics, University of Baghdad, College of  Science for Women, Baghdad, Iraq, India.
2Shahad Imad Abdulsalam, Ministry of Health, Al-Yarmok Teaching Hospital, M.Sc.  College of  Science for Woman, University of Baghdad, Iraq, India.
3Dr. Ihssan Subhi Nema, Assistant professor, in Neurosurgery, Alnahrain University, College of Medicine Department of Surgery, Baghdad, Iraq, India.
Manuscript received on February 21, 2015. | Revised Manuscript received on February 28, 2015. | Manuscript published on March 05, 2015. | PP: 11-14 | Volume-5 Issue-1, March 2015. | Retrieval Number: F2494014615/2015©BEIESP
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Abstract: The detection of brain strokes from Computed Tomography CT images needs convenient processing techniques starting from image enhancement to qualify the brain image by isolation process, region growing and logical operators (OR and AND). These methods with the help of the simplest segmentation process, which is the thresholding process, are used to extract a stroke region from the CT image of the brain. The median filter is applied to remove the noise from the image. The statistical features calculated using first-order histogram were utilized in the detection of the stroke region.
Keywords: Hemorrhage stroke; CT scan image; Brain segmentation; statistical features.