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Medical images classification for skin cancer using quantitative image features with optical coherence tomography
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作者 Wei Gao valery p.zakharov +3 位作者 Oleg O.Myakinin Ivan A.Bratchenko Dmitry N.Artemyev Dmitry V.Kornilin 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2016年第2期8-16,共9页
Optical coherence tomography(OCT)is employed in the diagnosis of skin cancer.Particularly,quantitative image features extracted from OCT images might be used as indicators to classify the skin tumors.In the present pa... Optical coherence tomography(OCT)is employed in the diagnosis of skin cancer.Particularly,quantitative image features extracted from OCT images might be used as indicators to classify the skin tumors.In the present paper,we investigated intensity-based,texture-based and fractalbased features for automatically classifying the melanomas,basal cell carcinomas and pigment nevi.Generalized estimating equations were used to test for differences between the skin tumors.A modified p value of<0.001 was considered statistically significant.Significant increase of mean and median of intensity and significant decrease of mean and median of absolute gradient were observed in basal cell carcinomas and pigment nevi as compared with melanomas.Significant decrease of contrast,entropy and fractal dimension was also observed in basal cell carcinomas and pigment nevi as compared with melanomas.Our results suggest that the selected quantitative image features of OCT images could provide useful information to differentiate basal cell carcinomas and pigment nevi from the melanomas.Further research is warranted to determine how this approach may be used to improve the classification of skin tumors. 展开更多
关键词 Optical coherence tomography skin tumor texture analysis fractal analysis differentiate box counting
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