Enhanced Detection of Cerebral Atherosclerosis Using Hybrid Algorithm of Image Segmentation
نویسندگان
چکیده
In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques. Major objective of this work is to detect cerebral atherosclerosis segmentation application. Detection some abnormal structures in body become difficult task complete with simple images. For expounding and distinguishing neural architecture brain an effective manner, MRI (Magnetic Resonance Imaging) one the most suitable significant technique. Here we on detection Cerebral Atherosclerosis from images patients. vascular disease causes narrowing arteries due buildup fatty plaque inside blood vessels brain. It leads Ischemic stroke if not diagnosed early. Stroke affects majorly old age people percentage affected women more compared men. Results: Preprocessing done using alpha trimmed mean filter which used remove noise also it enhances image. Segmentation K-means clustering, Contextual proposed Hybrid algorithm. Various parameters like Correlation, Pixel density, energy determined analysis that algorithm efficient.
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ژورنال
عنوان ژورنال: Intelligent Automation and Soft Computing
سال: 2023
ISSN: ['2326-005X', '1079-8587']
DOI: https://doi.org/10.32604/iasc.2023.025919