Dermoscopic Image Segmentation Using Fuzzy Techniques

Sowmya Devi

ISBN 10: 384435512X / ISBN 13: 9783844355123

Published by LAP Lambert Academic Publishing, 2012

About this Item

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.

Seller Inventory # 9783844355123

Bibliographic Details

• Title: Dermoscopic Image Segmentation Using Fuzzy Techniques
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 384435512X
• ISBN 13: 9783844355123
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 33D millimeters 220 millimeters width by 150 millimeters height by 33 millimeters depth
• Weight: 112 grams

About this title

Synopsis

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

About the Author

R.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 conferences.Her areas of interest includes Image Processing,Digital Electronics and Microprocessor.