Background: Blue-gray ovoids (B-GOs), a critical dermoscopic structure for basal cell carcinoma (BCC), offer an opportunity for automatic detection of BCC. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could afford accurate characterization and automatic recognition of B-GOs, furthering the goal of automatic BCC detection. This study utilizes a novel segmentation method to discriminate B-GOs from their benign mimics.
Methods: Contact dermoscopy images of 68 confirmed BCCs with B-GOs were obtained. Another set of 131 contact dermoscopic images of benign lesions possessing B-GO mimics provided a benign competitive set. A total of 22 B-GO features were analyzed for all structures: 21 color features and one size feature. Regarding segmentation, this study utilized a novel sector-based, non-recursive segmentation method to expand the masks applied to the B-GOs and mimicking structures. Results: Logistic regression analysis determined that blue chromaticity was the best feature for discriminating true B-GOs in BCC from benign, mimicking structures. Discrimination of malignant structures was optimal when the final B-GO border was approximated by a best-fit ellipse. Using this optimal configuration, logistic regression analysis discriminated the expanded and fitted malignant structures from similar benign structures with a classification rate as high as 96.5%.
Conclusions: Experimental results show that color features allow accurate expansion and localization of structures from seed areas. Modeling these structures as ellipses allows high discrimination of B-GOs in BCCs from similar structures in benign images.
P. Guvenc and R. W. LeAnder and S. Kefel and W. V. Stoecker and R. K. Rader and K. A. Hinton and S. M. Stricklin and H. S. Rabinovitz and M. C. Oliviero and R. H. Moss, "Sector Expansion and Elliptical Modeling of Blue-Gray Ovoids for Basal Cell Carcinoma Discrimination in Dermoscopy Images," Skin Research and Technology, vol. 19, no. 1, pp. e532-e536, John Wiley & Sons, Feb 2013.
The definitive version is available at https://doi.org/10.1111/srt.12006
Electrical and Computer Engineering
National Institutes of Health (U.S.). Small Business Innovation Research Program
Keywords and Phrases
Basal Cell Carcinoma; Dermoscopy; Region Growing; Skin Lesion; Artificial Intelligence; Color; Diagnosis; Image Analysis; Regression Analysis; Structural Optimization; Crystal Structure; Article; Blue Gray Ovoid; Cell Structure; Colorimetry; Epiluminescence Microscopy; Model; Algorithms; Carcinoma, Basal Cell; Colorimetry; Databases, Factual; Diagnosis, Differential; Humans; Logistic Models; Models, Biological; Neoplasms; Pattern Recognition, Automated; Skin Neoplasms; Computational Intelligence; Skin Lesion
International Standard Serial Number (ISSN)
Article - Journal
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