Abstract: A method for performing flow analysis in a target volume of a moving organ having a long axis, such as the heart, from 4D MR Flow volumetric image data set of such organ, wherein such data set comprises structural information and three-directional velocity information of the target volume over time, the devices, program products and methods comprising, under control of one or more computer systems configured with specific executable instructions: a) deriving from the 4D MR Flow volumetric image data set at least one derived image data set related to the long axis of the moving organ, for example, by using a multi planar reconstruction; b) determining at least one feature of interest in the 4D MR Flow volumetric image data set or in said derived image data set.

Abstract: A method for providing guidance in Cardiac Resynchronization Therapy (CRT) comprising: a) providing image data sets of the heart of a patient; b) creating a three-dimensional (3D) anatomical model of the cardiac structures; c) calculating myocardium infarct scar distribution; d) calculating heart mechanical activation data; e) superimposing the scar distribution and the mechanical activation data on the 3D anatomical model to obtain a 3D roadmap model including anatomical geometry and mechanical activation data. A corresponding device and computer program are also model disclosed.

Abstract: Method for assessing a regurgitant flow through a valve into a moving object from a sequence of consecutive image frames of such object, which images are timely separated by a certain time interval, the method comprising the following steps: a) identifying in the images the object of interest; b) augmenting the images to compensate for protocol intensity variation and/or motion and/or background; c) making a time-analysis of augmented images to obtain time-density curve or curves, wherein time-density curves represent a time-evolution of pixel brightness; d) determining a plurality of parameters related to such time-density curve or curves; e) weighting such parameters to provide indications on the regurgitant flow. A corresponding apparatus and computer program are also disclosed.

Abstract: A method for tracking position of features of a moving organ from at least one sequence of image frames of the moving organ involves identifying at least a first feature and a second feature of the organ in a reference image frame. Positions of the first and second features in other image frames are tracked in order to learn motion patterns of the first and second features. A dynamic geometric relation between the first and second features is determined. In the event that the first feature of the organ is obscured in a given image frame, position of the first feature in the given image frame is determined using position of the second feature in the given image frame and the dynamic geometric relation between the first and second features.

Abstract: Method for assessing a regurgitant flow through a valve into a moving object from a sequence of consecutive image frames of such object, which images are timely separated by a certain time interval, the method comprising the following steps: a) identifying in the images the object of interest; b) augmenting the images to compensate for protocol intensity variation and/or motion and/or background; c) making a time-analysis of augmented images to obtain time-density curve or curves, wherein time-density curves represent a time-evolution of pixel brightness; d) determining a plurality of parameters related to such time-density curve or curves; e) weighting such parameters to provide indications on the regurgitant flow. A corresponding apparatus and computer program are also disclosed.

Abstract: A method for tracking position of features of a moving organ from at least one sequence of image frames of the moving organ, comprising: a) identifying at least a first feature and a second feature of the organ in a reference image frame of the at least one sequence of image frames; b) tracking position of the first and second features in other image frames of the at least one sequence of image frames in order to learn motion patterns of the first and second features; c) determining a dynamic geometric relation between the first and second features; and d) in the event that the first feature of the organ is obscured in a given image frame of the at least one sequence of image frames, determining position of the first feature in the given image frame using position of the second feature in the given image frame and the dynamic geometric relation between the first and second features as determined in step c). A corresponding apparatus and computer product are also disclosed and claimed.

Abstract: Method for quantitative analysis of a tree or part of a tree of recursively splitting tubular organs, the method comprising the following steps:—providing a 3D model of said tree or part of said tree, such 3D model giving a representation of the surface of the lumen wall of the tubular organs forming the tree or part of the tree;—defining the 3D centrelines of said tree or part of the tree;—identifying the branches of the tree;—identifying N-furcations of the tree or part of the tree, an N-furcation being a part of the tree where a proximal tubular organ branches into two or more distal tubular organs, further comprising the step of:—dividing, independently from the modality used for obtaining the 3D model, each branch in one or more regions, such regions being of two different types, named single vessel region and splitting region, different cross-section surfaces being defined in such regions, wherein the splitting regions can exist at the proximal side of a branch as well as at the distal side of said bran

Abstract: A method is disclosed to accurately determine spatial parameters (for example, the diameter, cross-sectional area and segment length) of bodily structures like human arteries. This is done by determining the three-dimensional position of these structures from two monoplane X-ray angiographic images obtained at arbitrary but different orientations with respect to the structure of interest. The images may be taken at a different moment, so a monoplane X-ray system can be used. Movement of the structure of interest in between the two X-ray exposures is allowed. The three-dimensional information obtained this way is subsequently used to correct the measurements of above mentioned parameters for commonly encountered error sources.