An analytic model is described for application in ultrasonic tissue characterization. The model is applicable to clinical broadband pulse echo systems. It treats spectra derived from received echo signals and relates them to physical tissue properties. The model can be applied to deterministic tissue structures (e.g., retinal detachments, larger blood vessels, and surface layers of the kidney) and to stochastic tissue structures (e.g., various tumors). The beam patterns included in the model are those generated by focused transducers typically used in high-resolution clinical ultrasound. Appropriate calibration procedures are also treated; these are needed for interpretation of absolute spectral parameters. The results obtained with the analytic model have been used to design a digital processing system and the associated techniques which are now being applied during examinations of the eye and abdominal organs. The results have proven useful in interpreting data from various types of tissues. To illustrate the application of these results, representative clinical data, obtained from the digital system, are presented for two types of tissue architectures. The first case is a detached retina representing a deterministic structure characterized by well-defined thickness and reflection coefficients. The second case is asteroid hyalosis and represents a stochastic entity in which the positions of small scattering particles are best described in statistical terms, and characterization is accompanied by means of normalized power spectra.

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This paper describes Digital Imaging Fiber-Optic Translllumination (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.

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.

Reliable differentiation between early MM and AMN with high sensitivity is possible using machine vision techniques to analyze digitized dermoscopic lesion images.

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.

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