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    ARTICLE

    Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

    Mohammed Jasim Mohammed Jasim1, Bzar Khidir Hussan2, Subhi R. M. Zeebaree3,*, Zainab Salih Ageed4

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3677-3693, 2023, DOI:10.32604/cmc.2023.037363

    Abstract The major mortality factor relevant to the intestinal tract is the growth of tumorous cells (polyps) in various parts. More specifically, colonic polyps have a high rate and are recognized as a precursor of colon cancer growth. Endoscopy is the conventional technique for detecting colon polyps, and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss rate. The automated diagnosis of polyps in a computer-aided diagnosis (CAD) method is implemented using statistical analysis. Nowadays, Deep Learning, particularly through Convolution Neural networks… More >

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