TY - JOUR
T1 - Detection of basal cell carcinoma using color and histogram measures of semitranslucent areas
AU - Stoecker, William V.
AU - Gupta, Kapil
AU - Shrestha, Bijaya
AU - Wronkiewiecz, Mark
AU - Chowdhury, Raeed
AU - Stanley, Joe R.
AU - Xu, Jin
AU - Moss, Randy H.
AU - Celebi, Emre M.
AU - Rabinovitz, Harold S.
AU - Oliviero, Margarat
AU - Malters, Joseph M.
AU - Kolm, Isabel
PY - 2009
Y1 - 2009
N2 - Background: Semitranslucency, defined as a smooth, jelly-like area with varied, near-skin-tone color, can indicate a diagnosis of basal cell carcinoma (BCC) with high specificity. This study sought to analyze potential areas of semitranslucency with histogram-derived texture and color measures to discriminate BCC from non-semitranslucent areas in non-BCC skin lesions. Methods: For 210 dermoscopy images, the areas of semitranslucency in 42 BCCs and comparable areas of smoothness and color in 168 non-BCCs were selected manually. Six color measures and six texture measures were applied to the semitranslucent areas of the BCC and the comparable areas in the non-BCC images. Results: Receiver operating characteristic (ROC)curve analysis showed that the texture measures alone provided greater separation of BCC from non-BCC than the color measures alone. Statistical analysis showed that the four most important measures of semitranslucency are three histogram measures: contrast, smoothness, and entropy, and one color measure: blue chromaticity. Smoothness is the single most important measure. The combined 12 measures achieved a diagnostic accuracy of 95.05% based on area under the ROC curve. Conclusion: Texture and color analysis measures, especially smoothness, may afford automatic detection of BCC images with semitranslucency.
AB - Background: Semitranslucency, defined as a smooth, jelly-like area with varied, near-skin-tone color, can indicate a diagnosis of basal cell carcinoma (BCC) with high specificity. This study sought to analyze potential areas of semitranslucency with histogram-derived texture and color measures to discriminate BCC from non-semitranslucent areas in non-BCC skin lesions. Methods: For 210 dermoscopy images, the areas of semitranslucency in 42 BCCs and comparable areas of smoothness and color in 168 non-BCCs were selected manually. Six color measures and six texture measures were applied to the semitranslucent areas of the BCC and the comparable areas in the non-BCC images. Results: Receiver operating characteristic (ROC)curve analysis showed that the texture measures alone provided greater separation of BCC from non-BCC than the color measures alone. Statistical analysis showed that the four most important measures of semitranslucency are three histogram measures: contrast, smoothness, and entropy, and one color measure: blue chromaticity. Smoothness is the single most important measure. The combined 12 measures achieved a diagnostic accuracy of 95.05% based on area under the ROC curve. Conclusion: Texture and color analysis measures, especially smoothness, may afford automatic detection of BCC images with semitranslucency.
KW - Basal cell carcinoma
KW - Dermoscopy
KW - Image analysis
KW - Semitranslucency
KW - Texture
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U2 - 10.1111/j.1600-0846.2009.00354.x
DO - 10.1111/j.1600-0846.2009.00354.x
M3 - Article
C2 - 19624424
AN - SCOPUS:67650675059
SN - 0909-752X
VL - 15
SP - 283
EP - 287
JO - Skin Research and Technology
JF - Skin Research and Technology
IS - 3
ER -