Abstract
An apparatus for distinguishing benign from malignant tumors in ultrasonic images of candidate tissue taken from a patient. A region of interest is located and defined on the ultrasonic image, including substantially all of the candidate tissue and excluding substantially all the normal tissue. The region of interest is digitized, generating an array of pixels intensity values. A first features is generated from the arrays of pixels corresponding to the angular second moment of the pixel intensity values. A second feature is generated from the array of pixels corresponding to the inverse contrast of the pixel intensity values. A third feature is generated from the array of pixels corresponding to the short run emphasis of the pixel intensity values. The first, second and third feature values are provided to a neural network. A set of trained weights are applied to the feature values, which generates a network output between 0 and 1, whereby the output values tend toward 1 when the candidate tissue is malignant and the output values tend toward 0 when the candidate tissue is benign.
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