Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images

Abstract

An automated method for analyzing a nodule and a computer storage medium storing computer instructions by which the method can be implemented when the instructions are loaded into a computer to program the computer. The method includes obtaining a digital image including the nodule; segmenting the nodule to obtain an outline of the nodule, including generating a difference image from chest image, identifying image intensity contour lines representative of respective image intensities in a region of interest including the nodule, and obtaining an outline of the nodule based on the image intensity contours; extracting features of the nodule based on the outline; applying features including the extracted features to at least one image classifier; and determining a likelihood of malignancy of the nodule based on the output of the at least one classifier. In one embodiment, extracted features are applied to a linear discriminant analyzer and/or an artificial neural network analyzer, the outputs of which are thresholded and the nodule determined to be non-malignant if each classifier output is below the threshold. In another embodiment, a common nodule appearing in an x-ray chest image and a CT image is segmented in each image, features extracted based on the outlines of each segmented nodule in the respective x-ray chest and CT images, and the extracted features from the x-ray chest image and CT images merged as inputs to a common classifier, with the output of the common classifier indicating the likelihood of malignancy.

Dependencies are inferred from the claim text.