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Dermoscopic Image Segmentation Using Fuzzy Techniques


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  • Product Description

Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. This work explains the task of segmenting skin lesions in Dermoscopy images using various Fuzzy clustering techniques for the early diagnosis of Malignant Melanoma. Malignant Melanoma is the most frequent type of skin cancer and its incidence has been rapidly increasing over the last few decades. Dermoscopy is a non-invasive diagnosis technique for the observation of pigmented skin lesions used in dermatology. Dermoscopic images have great potential in the early diagnosis of malignant melanoma, but their interpretation is time consuming and subjective, even for trained dermatologists.The various Fuzzy clustering techniques used are Fuzzy C Means Algorithm (FCM), Possibilistic C Means Algorithm and Hierarchical C Means Algorithm. The segmented images are compared with the ground truth image using various parameters such as False Positive Error (FPE), False Negative Error (FNE), Coefficient of similarity, Spatial overlap and their performance is evaluated

Product Specifications
SKU :COC56890
AuthorSowmya Devi
Number of Pages64
Publishing Year2012-12-13T00:00:00.000
Edition1 st
Book TypeElectronics & communications engineering
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-06-08 00:00:00