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OverviewCervical cancer, the second most common cancer globally, is highly curable if detected early. However, rural areas face high mortality rates due to poor resources and limited screening programs. Automated diagnosis can address these gaps by distinguishing abnormal Pap smear cells based on nuclear shape. This study evaluates segmentation methods on the AGMC-TU Pap-Smear dataset, achieving a classification accuracy of 92.83% with SVM Linear and improving to 97.65% using optimized features and the FCM method. Accurate nucleus segmentation is crucial for reliable abnormal cell prediction, enhancing cervical cancer screening efficacy. Full Product DetailsAuthor: Bhabna dePublisher: LAP Lambert Academic Publishing Imprint: LAP Lambert Academic Publishing Dimensions: Width: 15.20cm , Height: 0.40cm , Length: 22.90cm Weight: 0.118kg ISBN: 9783659873713ISBN 10: 3659873713 Pages: 72 Publication Date: 29 November 2024 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: Available To Order We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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