Doctoral Dissertations
Automatic detection of lesion border and edge-related structures in dermoscopy images
Keywords and Phrases
Dermoscopy
Abstract
"Early detection of malignant melanoma is critical because early stage diagnosis results in a higher survival rate. As pre-processing steps of digital dermoscopy images in an automatic diagnosis system, line structure identification and lesion border identification algorithms are important for accuracy of diagnosis. This work presents the methodology and procedures to process dermoscopy images using computer vision and data mining methods. A watershed-based adaptive skin lesion border finder was developed and implemented for dermoscopy images...An improved SharpRazor algorithm was developed to remove hairs from dermoscopy images, based on a previously existing DullRazorʼ algorithm for hair removal...Work is also reported here on classifiers for detecting atypical pigment network in skin lesions based on texture"--Abstract, page iv.
Advisor(s)
Moss, Randy Hays, 1953-
Committee Member(s)
Beetner, Daryl G.
Samaranayake, V. A.
Stanley, R. Joe
Shrestha, Bijaya
Department(s)
Electrical and Computer Engineering
Degree Name
Ph. D. in Electrical Engineering
Publisher
University of Missouri--Rolla
Publication Date
Fall 2007
Journal article titles appearing in thesis/dissertation
- Skin lesion segmentation by an adaptive watershed flooding approach
- Adaptive morphological line structure segmentation on skin lesion images - SharpRazor, a software improvement of DullRazorʼ
- Detection of atypical texture features in early malignant melanoma
Pagination
xi, 83 pages
Note about bibliography
Includes bibliographical references.
Rights
© 2007 Xiaohe Chen, All rights reserved.
Document Type
Dissertation - Citation
File Type
text
Language
English
Subject Headings
Image processingMelanoma -- DiagnosisSkin -- Cancer -- Diagnosis
Thesis Number
T 9315
Print OCLC #
238657664
Recommended Citation
Chen, Xiaohe, "Automatic detection of lesion border and edge-related structures in dermoscopy images" (2007). Doctoral Dissertations. 1752.
https://scholarsmine.mst.edu/doctoral_dissertations/1752
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