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Automatic Segmentation of Brain CT scan Image to Identify Hemorrhages
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 40 - Number 10 |
| Year of Publication: 2012 |
| Authors: Bhavna Sharma, K. Venugopalan |
10.5120/4997-7271
|
Bhavna Sharma, K. Venugopalan . Automatic Segmentation of Brain CT scan Image to Identify Hemorrhages. International Journal of Computer Applications. 40, 10 ( February 2012), 1-4. DOI=10.5120/4997-7271
Abstract
Segmentation is required as a preliminary step in the analysis of medical images for computer aided diagnosis. For detecting tumors, edema, hemorrhage or any other abnormality given the complex structure of the brain, precise segmentation is crucial. CT scan is preferred method in traumatic brain injuries due to better contrast on bone, low cost and wide availability. This paper proposes fully automatic segmentation of brain CT images to identify hemorrhages. The method is comprised of three stages, preprocessing performed on the brain CT images, histogram based centroids initialization and finally the K-means clustering algorithm applied on the resultant image to segment the image in different clusters based on the intensity values of pixels. The method precisely segments the input image in exact clusters and analyzing those clusters hemorrhage can be identified.
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