Dermoscopic Image Segmentation Using by Devi Sowmya (7 results)
Language: English
Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG 2012
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Taschenbuch. Condition: Neu. Dermoscopic Image Segmentation Using Fuzzy Techniques | Sowmya Devi | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783844355123 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Language: English
Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG 2012
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Condition: New. Print on Demand pp. 64 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.
Language: English
Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG 2012
- Softcover
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Condition: New. PRINT ON DEMAND pp. 64.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Devi SowmyaR.Sowmya Devi is a graduate of Noorul Islam College of Engineering,Tamil Nadu. She received her M.E. from Noorul Islam University. She has published journals and has attended several conferen…ces.Her areas of interest incl.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
