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Abstract

A method and apparatus for directly identifying and characterizing input data derived from regions of interest in ultrasound images of organs in the presence of attenuation from interposed contrast agent, for the purpose of diagnosing abnormalities. The input data is classified into one of a number of classes depending upon the characteristics of that data, in order to distinguish normal conditions from abnormal conditions. The invention is based on the recognition that significant information relating to the health of tissue exists in regions of interest in ultrasound images in the presence of attenuation from interposed contrast agent. This information is in the form of backscatter speckle patterns that have 'texture' characteristics that are distinguishable in healthy versus diseased tissue. The invention classifies such patterns as probably normal or abnormal by means of an analysis system that may include a neural network system. The preferred embodiment of the present invention includes: (1) a data acquisition system for acquiring ultrasound image data indicative of a region of interest in the presence of attenuation from interposed contrast agent; (2) an optional signal conditioning stage to remove signals (e.g., noise) from the input data; and (3) an analysis system designed to detect 'texture' characteristics that distinguish healthy tissue from diseased tissue even in the presence of the contrast agent. The output classifies the input data in a uniform, unambiguous manner. The invention is preferably implemented as a computer program executing on a programmable computer.

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First Claim