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Title: Detection of pigment network in dermatoscopy images using texture analysis
Author (s): Anantha, Murali
Stoecker, William V.
Moss, Randy Hays
Department/Lab Affiliations: Electrical and Computer Engineering
Image Processing Laboratory
Keywords: Dermatoscopy
Energy masks
Image analysis
Melanoma
Pigment network
Texture
Issue Date: 2004
Publisher: BioMed Central
Citation: A. Murali, R. H. Moss, W. V. Stoecker. "Detection of Pigment Network in Dermatoscopy Images Using Texture Analysis", Computerized Medical Imaging and Graphics, Vol. 28, 2004, pp. 94-104, 2004.
Abstract: Dermatoscopy, also known as dermoscopy or epiluminescence microscopy (ELM), is a non-invasive, in vivo technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. ELM offers a completely new range of visual features. One such prominent feature is the pigment network. Two texture-based algorithms are developed for the detection of pigment network. These methods are applicable to various texture patterns in dermatoscopy images, including patterns that lack fine lines such as cobblestone, follicular, or thickened network patterns. Two texture algorithms, Laws energy masks and the neighborhood gray-level dependence matrix (NGLDM) large number emphasis, were optimized on a set of 155 dermatoscopy images and compared. Results suggest superiority of Laws energy masks for pigment network detection in dermatoscopy images. For both methods, a texel width of 10 pixels or approximately 0.22 mm is found for dermatoscopy images.
Type: Article - Journal
text
In Title: Computerized Medical Imaging and Graphics
Copyright Notice: Pre-print: author can archive; Post-print: author can archive;
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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http://www.biomedcentral.com/info/about/license
Publisher URL:
http://www.ncbi.nlm.nih.gov/pubmed/15249068
Link to this page:
http://scholarsmine.mst.edu/post_prints/DetectionOfPigmentNetworkInDermatoscopyIma_09007dcc8052c055.html



titleDetection of pigment network in dermatoscopy images using texture analysis
contributor.authorAnantha, Murali
contributor.authorStoecker, William V.
contributor.authorMoss, Randy Hays
contributor.deptlabElectrical and Computer Engineering
contributor.deptlabImage Processing Laboratory
contributor.sponsorNational Institute of Health
subjectDermatoscopy
subjectEnergy masks
subjectImage analysis
subjectMelanoma
subjectPigment network
subjectTexture
date.issued2004
publisherBioMed Central
identifier.citationA. Murali, R. H. Moss, W. V. Stoecker. "Detection of Pigment Network in Dermatoscopy Images Using Texture Analysis", Computerized Medical Imaging and Graphics, Vol. 28, 2004, pp. 94-104, 2004.
identifier.pub.URI
http://www.ncbi.nlm.nih.gov/pubmed/15249068
description.abstractDermatoscopy, also known as dermoscopy or epiluminescence microscopy (ELM), is a non-invasive, in vivo technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. ELM offers a completely new range of visual features. One such prominent feature is the pigment network. Two texture-based algorithms are developed for the detection of pigment network. These methods are applicable to various texture patterns in dermatoscopy images, including patterns that lack fine lines such as cobblestone, follicular, or thickened network patterns. Two texture algorithms, Laws energy masks and the neighborhood gray-level dependence matrix (NGLDM) large number emphasis, were optimized on a set of 155 dermatoscopy images and compared. Results suggest superiority of Laws energy masks for pigment network detection in dermatoscopy images. For both methods, a texel width of 10 pixels or approximately 0.22 mm is found for dermatoscopy images.
typeArticle - Journal
type.DCMITypetext
type.statusPostprint
rightsPre-print: author can archive; Post-print: author can archive;
rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
rights.URI
http://www.biomedcentral.com/info/about/license
relation.isPartOfComputerized Medical Imaging and Graphics
date.available2008-07-08T13:31:41Z
identifier.persist.URI
http://scholarsmine.mst.edu/post_prints/DetectionOfPigmentNetworkInDermatoscopyIma_09007dcc8052c055.html