DocumentCode :
186094
Title :
Automatic mobile segmentation of dermoscopy images using density based and fuzzy c-means clustering
Author :
Mendi, Engin ; Yogurtcular, Caner ; Sezgin, Yusuf ; Bayrak, Coskun
Author_Institution :
Dept. of Comput. Eng., KTO Karatay Univ., Konya, Turkey
fYear :
2014
fDate :
11-12 June 2014
Firstpage :
1
Lastpage :
6
Abstract :
Accurate identification and extraction of region of interest (ROI) in dermoscopy images play crucial role in diagnosis, and treatment of melanoma and other skin diseases. Human interpretation of dermoscopy images is not only tedious and time consuming task but also subjective. This fact has attracted numerous attentions for developing automated assessment tools. In this paper, we present lesion detection schemes in dermoscopy images on mobile platforms. The systems are based on density based clustering (DBSCAN) and fuzzy c-means (FCM) clustering and developed for Windows Phone and Android environments. We tested the systems on dermoscopy images and ROIs are successfully extracted. The proposed systems may improve the management of melanoma by providing automatic early monitoring of skin lesions that will assist clinical investigation.
Keywords :
biomedical optical imaging; cancer; feature extraction; fuzzy set theory; image segmentation; medical image processing; patient monitoring; skin; Android environments; DBSCAN; FCM; ROI extraction; Windows Phone; automated assessment tools; automatic early skin lesion monitoring; automatic mobile segmentation; density based clustering; dermoscopy images; fuzzy c-means clustering; lesion detection; melanoma diagnosis; melanoma treatment; region-of-interest identification; skin diseases; Cancer; Clustering algorithms; Image segmentation; Lesions; Malignant tumors; Skin; Smart phones;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Medical Measurements and Applications (MeMeA), 2014 IEEE International Symposium on
Conference_Location :
Lisboa
Print_ISBN :
978-1-4799-2920-7
Type :
conf
DOI :
10.1109/MeMeA.2014.6860020
Filename :
6860020
Link To Document :
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