COMPUTERIZED DETECTION OF LUNG NODULES USING ENERGY-SUBTRACTED SOFT-TISSUE AND STANDARD CHEST IMAGES

A method, system and computer readable medium configured for computerized detection of lung abnormalities, including obtaining a standard digital chest image and a soft-tissue digital chest image; generating a first difference image from the standard digital chest image and a second difference image from the soft-tissue digital chest image; identifying candidate abnormalities in the first and second difference images; extracting from the standard digital chest image and the first difference image predetermined first features of each of the candidate abnormalities identified in the first difference image; extracting from the soft-tissue digital chest image and the second difference images predetermined second features of each of the candidate abnormalities identified in the second difference image; analyzing the extracted first features and the extracted second features to identify and eliminate false positive candidate abnormalities respectively corresponding thereto; applying extracted features from remaining candidate abnormalities derived respectively from the first and second difference images and remaining after the elimination of the false positive candidate abnormalities to respective artificial neural networks to eliminate further false positive candidate abnormalities; performing a logical OR operation of the candidate abnormalities derived respectively from the first and second difference images and remaining after the elimination of the false positive candidate abnormalities; and outputting a signal indicative of a result of performing the logical OR operation. The logical OR combination, of locations of the candidate abnormalities detected in the first difference image and the second difference image, yields an improved detection sensitivity (over 90%) and only slightly increased false positives rate (3.2 false positives per chest image).