"The blood vessels are part of the circulatory system and function to transport blood throughout the body. Vessels have their own features such as distinctive color compared to surrounding skin as well as distinctive curved and/or linear shape. Telangiectases are small dilated blood vessels near the surface of the skin or mucous membranes, measuring between 0.5 and 1 millimeter in diameter. In this research, image analysis techniques are investigated to detect vessels in dermoscopy skin lesion images. Machine vision and neural network methods are explored to discriminate skin lesions containing telangiectases from those containing normal vessels. A vessels Detection technique is implemented firstly to find the possible vessels in dermatology skin lesion images. In addition, a noise filtering technique is applied, which filters out the "noise" such as hair, bubble and so one, according to their own features. Based on the fact that some of the images are fuzzy, a contrast enhancement technique can be added to increase the contrast. After obtaining the final masked regions containing vessel-like structures, features are computed to facilitate the discrimination of skin lesion with normal vessels from lesions containing telangiectases. The features are mostly about the number, shape and size of telangiectases mask"--Abstract, page iii.
Stanley, R. Joe
Stoecker, William V.
Moss, Randy Hays, 1953-
Electrical and Computer Engineering
M.S. in Computer Engineering
Stoecker and Associates
Missouri University of Science and Technology
ix, 47 pages
© 2009 Beibei Cheng, All rights reserved.
Thesis - Open Access
Basal cell carcinoma -- Diagnosis -- Computer programs
Image processing -- Computer programs
Skin -- Cancer -- Diagnosis -- Computer programs
Print OCLC #
Electronic OCLC #
Link to Catalog Record
Cheng, Beibei, "Automatic vessel and telangiectases analysis in dermoscopy skin lesion images" (2009). Masters Theses. 4654.