Abstract: A method for visualizing the anatomy of a region of interest of a tubular-shaped organ based on acquired three-dimensional image slices of the region of interest. Prior to segmentation, reference markers are positioned interactively in the image slices, a minimum curvature path connecting the reference markers is automatically extracted and cross-sectional images are interpolated along a plane normal to a tangent vector of the minimum curvature path. A segmented area corresponding to the region of interest is then delimited in each cross-sectional image and, using this segmented area, a three-dimensional surface representation of the region of interest is computed to readily quantify attributes, such as a maximal diameter and a volume, of the region of interest. When the image sets are acquired in different imaging geometries, the image sets may further be co-registered prior to segmentation, resulting in image sets superimposed in the same geometrical reference frame.

Abstract: A segmentation method is provided for the automated segmentation of spot-light structures into D images allowing precise quantification and classification of said structures and said images, based on a plurality of criteria, and further allowing the automated identification of multi-spot based patterns present in one or a plurality of images. In a preferred embodiment, the invention is used for the analysis of 2D gel electrophoresis images, with objective of quantifying protein expressions and for allowing sophisticated multi-protein pattern based image data mining, as well as image matching, registration, and automated classification.

Abstract: An orthopedic magnetic resonance imaging system is disclosed. This system includes a source of magnetic resonance imaging data sets resulting from successive magnetic resonance imaging acquisitions from a diseased joint of a patient. A segmentation module segments surfaces in the joint based on information contained within at least one of the data sets, and a registration module spatially registers, in three dimensions, information represented by a first of the data sets with respect to information represented by one or more further data sets for the same patient. A comparison module detects differences between information represented by the data sets caused by progression of the disease in the joint of the patient between acquisitions. A cross-patient comparison module can compare detected differences for the patient with detected differences for at least one other patient.

Abstract: An orthopedic magnetic resonance imaging system is disclosed. This system includes a source of magnetic resonance imaging data sets resulting from successive magnetic resonance imaging acquisitions from a diseased joint of a patient. A segmentation module segments surfaces in the joint based on information contained within at least one of the data sets, and a registration module spatially registers, in three dimensions, information represented by a first of the data sets with respect to information represented by one or more further data sets for the same patient. A comparison module detects differences between information represented by the data sets caused by progression of the disease in the joint of the patient between acquisitions. A cross-patient comparison module can compare detected differences for the patient with detected differences for at least one other patient.