Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study.

BACKGROUND: Differentiation of melanoma from melanocytic nevi is difficult even for skin cancer specialists. This motivates interest in computer-assisted analysis of lesion images. OBJECTIVE: Our purpose was to offer fully automatic differentiation of melanoma from dysplastic and other melanocytic nevi through multispectral digital dermoscopy. METHOD: At 4 clinical centers, images were taken of pigmented lesions suspected of being melanoma before biopsy. Ten gray-level (MelaFind) images of each lesion were acquired, each in a different portion of the visible and near-infrared spectrum. The images of 63 melanomas (33 invasive, 30 in situ) and 183 melanocytic nevi (of which 111 were dysplastic) were processed automatically through a computer expert system to separate melanomas from nevi. The expert system used either a linear or a nonlinear classifier. The "gold standard" for training and testing these classifiers was concordant diagnosis by two dermatopathologists. RESULTS: On resubstitution, 100% sensitivity was achieved at 85% specificity with a 13-parameter linear classifier and 100%/73% with a 12-parameter nonlinear classifier. Under leave-one-out cross-validation, the linear classifier gave 100%/84% (sensitivity/specificity), whereas the nonlinear classifier gave 95%/68%. Infrared image features were significant, as were features based on wavelet analysis. CONCLUSION: Automatic differentiation of invasive and in situ melanomas from melanocytic nevi is feasible, through multispectral digital dermoscopy.

Precision of automatic measurements of pigmented skin lesion parameters with a MelaFind(TM) multispectral digital dermoscope.

The purpose of this study was to assess the precision of automatic computerized measurement of parameters that may be useful in the differentiation of malignant melanoma from benign pigmented skin lesions, and also to determine the feasibility of quantitative monitoring of skin lesions over time. Ten independent sequences of images were acquired with a MelaFind multispectral digital dermoscope for each of 12 benign or malignant pigmented skin lesions. The sequences of images were processed automatically to provide 10 independent measurements of the various parameters for each lesion. Parameters included lesion area, greatest 'diameter', perimeter, reflectance and asymmetry. The precision of each parameter determination was computed from the mean and standard deviation of the 10 measurements of that parameter. The relative errors in determining the lesion area, 'diameter' and perimeter were found to be 6%, 3% and 4%, respectively. Other lesion parameters that are used in differentiating melanomas from benign skin lesions were also analysed as a function of wavelength. In the blue band (about 430 nm) the relative error was about 7% for the mean lesion reflectance and about 7% for the asymmetry parameter. These results demonstrate the feasibility of using MelaFind for objective quantitative monitoring of changes in pigmented skin lesions over time. As suggested by some studies, such information is useful in the early detection of malignant melanoma. The results show that parameters obtained automatically from MelaFind images are sufficiently precise to allow pertinent parameters to be used to classify pigmented skin lesions.

Wavelet representations for monitoring changes in teeth imaged with digital imaging fiber-optic transillumination.

Digital imaging fiber-optic transillumination (DI-FOTI) is a novel method to detect and monitor dental caries, using light, a charge-coupled device (CCD) camera, and computer-controlled image acquisition. The advantages of DIFOTI over radiography include: no ionizing radiation, no film, real-time diagnosis, and higher sensitivity in detection of early lesions not apparent to X-ray, as demonstrated in vitro. Here, we present a method of processing DIFOTI images, acquired at different times, for monitoring changes. Of central importance to this application is pattern matching of image frames that is invariant to translation and rotation of a tooth, relative to the field of view of the imaging camera, and that is robust to changes in illumination source intensity. Our method employs: 1) wavelet modulus maxima representations for segmentation of teeth images; 2) first and second moments of gray level representations of DIFOTI images in the spatial domain, to estimate tooth location and orientation; and 3) multiresolution wavelet magnitude representations for quantitative monitoring. Even with illumination source intensity variation, it is demonstrated in vitro that such wavelet representations can facilitate detection of simulated clinical changes in light transmission that cannot be detected in the spatial domain.

Assessment of dental caries with Digital Imaging Fiber-Optic TransIllumination (DIFOTI): in vitro study.

This paper describes Digital Imaging Fiber-Optic TransIllumination (DIFOTI-TM), a new method for the reliable detection of dental caries. Images of teeth obtained through visible-light, fiber-optic transillumination (FOTI) are acquired with a digital CCD camera, and sent to a computer for analysis with dedicated algorithms. The algorithms were developed to facilitate the location and diagnosis of carious lesions by the operator in real time, and provide quantitative characterization for monitoring of the lesions. The DIFOTI method has been tested by imaging teeth in vitro. The results suggest the superior sensitivity of DIFOTI for detection of approximal, occlusal and smooth-surface caries vis-à-vis radiological imaging.