Abstract: A method for computer-assisted interpretation of medical images that factor in characteristics of an individual performing the interpretation. The method automatically determines and/or incorporates prevalence-based computer analysis based on an estimated likelihood of a pathological state, e.g., a malignancy. A system implementing the method includes the calculation of features or other characteristics of images in a known database, calculation of features of an unknown case, calculation of the probability (or likelihood) of disease state, calculation of the modified computer output that includes the internal prevalence (or internal decision-making process) of the user (or group of users), and output of the result.

Abstract: A method for in-room computer reconstruction of a three-dimensional (3-D) coronary arterial tree from routine biplane angiograms acquired at arbitrary angles and without using calibration objects.

Abstract: A method for automated analysis of abnormalities in the form of lesions and parenchymal distortions using digital images, including generating image data from respective of digital images derived from at least one selected portion of an object, for example, from mammographical digital images of the left and right breasts. The image data from each of the digital images are then correlated to produce correlated data in which normal anatomical structured background is removed. The correlated data is then searched using one or more predetermined criteria to identify in at least one of the digital images an abnormal region represented by a portion of the correlated data which meets the predetermined criteria. The location of the abnormal region is then indicated, and the indicated location is then subjected to classification processing to determine whether or not the abnormal region is benign or malignant. Classification is performed based on the degree of spiculations of the identified abnormal region.

Abstract: A novel method for determination of 3-D structure in biplane angiography, including determining the distance of a perpendicular line from the focal spots of respective x-ray sources to respective image planes and defining the origin of each biplane image as the point of intersection with the perpendicular line thereto, obtaining two biplane digital images at arbitrary orientations with respect to an object, identifying at least 8 points in both images which correspond to respective points in the object, determining the image coordinates of the 8 or more identified object points in the respective biplane images, constructing a set of linear equations in 8 unknowns based on the image coordinates of the object points and based on the known focal spot to image plane distances for the two biplane images; solving the linear equations to yield the 8 unknowns, which represent the fundamental geometric parameters of the biplane imaging system; using the fundamental parameters to calculate the 3-dimensional positions o