The beneficial techniques in preprocessing step of skin cancer detection system comparing

Hoshyar, AN; Al-Jumaily, A

The beneficial techniques in preprocessing step of skin cancer detection system comparing

Hoshyar, AN Al-Jumaily, A

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Publication Type:: Journal Article
Citation:: Procedia Computer Science, 2014, 42 (C), pp. 25 - 31
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Hoshyar, AN	en_US
dc.contributor.author	Al-Jumaily, A https://orcid.org/0000-0003-0297-2463	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Procedia Computer Science, 2014, 42 (C), pp. 25 - 31	en_US
dc.identifier.uri	http://hdl.handle.net/10453/34997
dc.description.abstract	© 2014 The Authors. Automatic diagnostics of skin cancer is one of the most challenging problems in medical image processing. It helps physicians to decide whether a skin melanoma is benign or malignant. So, determining the more efficient methods of detection to reduce the rate of errors is a vital issue among researchers. Preprocessing is the first stage of detection to improve the quality of images, removing the irrelevant noises and unwanted parts in the background of the skin images. The purpose of this paper is to gather the preprocessing approaches can be used in skin cancer images. This paper provides good starting for researchers in their automatic skin cancer detections.	en_US
dc.relation.ispartof	Procedia Computer Science	en_US
dc.relation.isbasedon	10.1016/j.procs.2014.11.029	en_US
dc.title	The beneficial techniques in preprocessing step of skin cancer detection system comparing	en_US
dc.type	Journal Article
utslib.citation.volume	C	en_US
utslib.citation.volume	42	en_US
utslib.for	080101 Adaptive Agents and Intelligent Robotics	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	10 Technology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.issue	C	en_US
pubs.publication-status	Published	en_US
pubs.volume	42	en_US

Abstract:

© 2014 The Authors. Automatic diagnostics of skin cancer is one of the most challenging problems in medical image processing. It helps physicians to decide whether a skin melanoma is benign or malignant. So, determining the more efficient methods of detection to reduce the rate of errors is a vital issue among researchers. Preprocessing is the first stage of detection to improve the quality of images, removing the irrelevant noises and unwanted parts in the background of the skin images. The purpose of this paper is to gather the preprocessing approaches can be used in skin cancer images. This paper provides good starting for researchers in their automatic skin cancer detections.

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http://hdl.handle.net/10453/34997