Computer Based Melanocytic and Nevus Image Enhancement and Segmentation
Joint Authors
Jamil, Uzma
Akram, M. Usman
Abbas, Sarmad
Saleem, Kashif
Khalid, Shehzad
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Digital dermoscopy aids dermatologists in monitoring potentially cancerous skin lesions.
Melanoma is the 5th common form of skin cancer that is rare but the most dangerous.
Melanoma is curable if it is detected at an early stage.
Automated segmentation of cancerous lesion from normal skin is the most critical yet tricky part in computerized lesion detection and classification.
The effectiveness and accuracy of lesion classification are critically dependent on the quality of lesion segmentation.
In this paper, we have proposed a novel approach that can automatically preprocess the image and then segment the lesion.
The system filters unwanted artifacts including hairs, gel, bubbles, and specular reflection.
A novel approach is presented using the concept of wavelets for detection and inpainting the hairs present in the cancer images.
The contrast of lesion with the skin is enhanced using adaptive sigmoidal function that takes care of the localized intensity distribution within a given lesion’s images.
We then present a segmentation approach to precisely segment the lesion from the background.
The proposed approach is tested on the European database of dermoscopic images.
Results are compared with the competitors to demonstrate the superiority of the suggested approach.
American Psychological Association (APA)
Jamil, Uzma& Akram, M. Usman& Khalid, Shehzad& Abbas, Sarmad& Saleem, Kashif. 2016. Computer Based Melanocytic and Nevus Image Enhancement and Segmentation. BioMed Research International،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1097030
Modern Language Association (MLA)
Jamil, Uzma…[et al.]. Computer Based Melanocytic and Nevus Image Enhancement and Segmentation. BioMed Research International No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1097030
American Medical Association (AMA)
Jamil, Uzma& Akram, M. Usman& Khalid, Shehzad& Abbas, Sarmad& Saleem, Kashif. Computer Based Melanocytic and Nevus Image Enhancement and Segmentation. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1097030
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097030