Optimization of quantitative sonographic diagnostic analysis of breast lesions

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Abstract
The purpose of this study was to enhance the ability of quantitative sonography to distinguish between B-scan images of malignant and benign lesions of the breast. Several second-order pixel gray level statistics have been used to achieve a good but not acceptable diagnostic accuracy in characterizing breast lesions. Therefore, this study sought to optimize the diagnostic accuracy of second order statistics. The co-occurrence matrix is the most useful second-order statistic so far studied. It is an estimate of the joint probability distribution of gray levels of two pixels separated by a given distance and orientation. Several distances and orientations have been tried previously, but no systematic attempt had been made to find the optimum parameters for diagnosis. In this study, co-occurrence statistics of malignant and benign lesion images were determined as a function of distance and orientation. In particular, the correlation function was modeled as a separable, exponential function, first order for increments in both the x and y directions. Model parameters were used as features for discriminating benign from cancer lesions. An attempt was made to optimize the features by excluding the noisy data from the fit and again using the model parameters.

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