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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1109/ebbt.2...
Article . 2017 . Peer-reviewed
License: STM Policy #29
Data sources: Crossref
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Automatic skin lesion segmentation

Authors: Haydar Ozkan; Reyhan Gurleyen; Elif Usta; Raziye Kubra Kumrular;

Automatic skin lesion segmentation

Abstract

In the modern world, cancer has increasingly become a health problem. It has been listed as the first three disease among the ‘cause-known deaths’ in our country. Malignant Melanoma, one of the skin cancer types, is the cause of 75% of all skin cancer related deaths even though it is 4% of all skin cancer cases. The examination of the diseases are diagnosed through visual inspections by the dermatologists. This brings the possibility of human error. In this study, a computer based segmentation system is developed to assist the expert dermatologists for determining whether the lesions on the skin are cancerous or not. The edges of lesions on the original images is drawn by enhancing and segmenting the lesions via image processing techniques, since lesions' shapes, color distributions and edges are important parameters for cancer determination process. In this way, the error rates are reduced by making it easier for the dermatologist to examine the lesions and make decisions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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