Abstract
Computed tomographic (CT) images are widely used in the diagnosis of stroke. The objective is to find the stoke area from a CT brain image and also improve the visual quality. The proposed algorithm helps to detect the stoke part in the absence of radiologist or doctors. Seed region growing (SRG) technique is the most popular method for segmentation of medical images because of high-level knowledge of anatomical structures in seed selection process. The proposed method consists of three steps: preprocessing, feature extraction, and segmentation. Feature extraction is done based on texture using the Gabor filter, and segmentation is done using SRG algorithm.
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Neethu, S., Venkataraman, D. (2015). Stroke Detection in Brain Using CT Images. In: Suresh, L., Dash, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 324. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2126-5_42
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DOI: https://doi.org/10.1007/978-81-322-2126-5_42
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