The feasibility of smartphones for in vivo skin autofluorescence imaging has been investigated. Filtered autofluorescence images from the same tissue area were periodically captured by a smartphone RGB camera with subsequent detection of fluorescence intensity decreasing at each image pixel for further imaging the planar distribution of those values. The proposed methodology was tested clinically with 13 basal cell carcinoma and 1 atypical nevus. Several clinical cases and potential future applications of the smartphone-based technique are discussed.
A clinical trial on the autofluorescence imaging of skin lesions comprising 16 dermatologically confirmed pigmented nevi, 15 seborrheic keratosis, 2 dysplastic nevi, histologically confirmed 17 basal cell carcinomas and 1 melanoma was performed. The autofluorescence spatial properties of the skin lesions were acquired by smartphone RGB camera under 405 nm LED excitation. The diagnostic criterion is based on the calculation of the mean autofluorescence intensity of the examined lesion in the spectral range of 515 nm-700 nm. The proposed methodology is able to differentiate seborrheic keratosis from basal cell carcinoma, pigmented nevi and melanoma. The sensitivity and specificity of the proposed method was estimated as being close to 100%. The proposed methodology and potential clinical applications are discussed in this article.
Z e n t r a l i n s t i t u t f u r A s t r o p h y s i k d e r A k a d e m i e d e r W i s s c n s c l i a f t e n d e r D U R'I'hc mechanical and electronic tlcvice of thc microphotometer is tlcscribcd. The on-line d a t a compression is pcrformed in t h c domain of t h e H A A R transform of thc mcasurcment points. This method provides a fast treatment of t h e measurement d a t a in the computer and changes t h e large d a t a material sampled in equidistant stcps wliosc width can bc chosen b y t h c seeing condition into a non-cquidistant grid whose widths depend only on t h e characteristiclcngtli of t h e signal. The grain noise is climinatcd. An automatical discrimination bctwecn stars and galaxies is possible. T h e accuracy of thc photoinctry was tested hy comparing with t h c photoelectrically detcrminerl B-brightness distribution of M 81.
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