Abstract: A medical image annotation system for analyzing a medical image. A plurality of image annotation tools are provided by the image annotation system, each of which is configured to perform, for one or more regions of interest of the medical image, at least a portion of an annotation. A recording module of the image annotation system is configured to record, for each of the regions of interest, interactions which are performed using the image annotation tools. The image annotation system is configured to compute an image annotation complexity metric for each of the regions of interest, based on the recorded interactions. Further, a presentation of the annotation tools by the user interface is indicative of an order, wherein the order is changed in response to the region of interest from which the user input is currently received.

Abstract: A system SY for determining a position of an OCT or IVUS catheter CA in a vasculature VA. The system SY includes a map-providing unit MPU, a data-providing unit DPU, and a comparator unit COMP. The map-providing unit is configured to provide a reference map SOM including reference measurement data at each of a plurality of positions P1 . . . k of the OCT or IVUS catheter CA in the vasculature VA. The data-providing unit DPU is configured to provide actual measurement data from an actual position in the vasculature VA. The comparator unit COMP is configured to determine from the plurality of positions P1 . . . k of the OCT or IVUS catheter in the vasculature, a position Pn?1 . . . k that corresponds to the actual position in the vasculature, based on a comparison of the actual measurement data and the reference measurement data. The reference measurement data and the actual measurement data are either i) OCT data or ii) IVUS data.

Abstract: The present invention relates to a device (1) for fractional flow reserve determination. The device (1) comprises a model generator (10) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor (20) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner (30) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

Abstract: A computing system (118) includes a computer readable storage medium (122) with computer executable instructions (124), including a biophysical simulator (126), and a reference location (128), and a processor (120) configured to the biophysical simulator and simulate a reference FFR value at a predetermined location along a segmented coronary vessel indicated by the reference location. A computer readable storage medium encoded with computer readable instructions, which, when executed by a processor of a computing system, causes the processor to simulate a reference FFR value at a predetermined location along a segmented coronary vessel indicated by a predetermined reference location. A method including simulating a reference FFR value at a predetermined location along a segmented coronary vessel indicated by a predetermined reference location.

Abstract: A computing system (126) includes a computer readable storage medium (130) with computer executable instructions (128), including: a segmentation standardizer (120) configured to determine a standardized vascular tree from a segmented vascular tree segmented of volumetric image data and a predetermined set of pruning rules (206), and a biophysical simulator (122) configured to perform a biophysical simulation based on the standardized vascular tree. The computing system further includes a processor (124) configured to execute the segmentation standardizer to determine the standardized vascular tree from the segmented vascular tree segmented of volumetric image data and the predetermined set of pruning rules, and configured to execute the biophysical simulator to perform a biophysical simulation based on the standardized vascular tree. The computing system further includes a display configured to display at least one of the standardized vascular tree and a result of the biophysical simulation.

Abstract: The present invention relates to an apparatus (26) and a method for determining a fractional flow reserve. For this purpose, a new personalized hyperemic boundary condition model is provided. The personalized hyperemic boundary condition model is used to condition a parametric model for a simulation of a blood flow in a coronary tree (34) of a human subject. As a basis for the personalized hyperemic boundary condition 5 model, a predefined hyperemic boundary condition model is used, which represents empirical derived hyperemic boundary condition parameters. However, these empirical hyperemic boundary condition parameters are not specific for a human subject under examination. In order to achieve a specification of the respective predefined hyperemic boundary condition model, specific human subject features are derived from a volumetric image of the coronary 10 tree of the human subject.

Abstract: A method is provided for generating a deformable model (300) for segmenting an anatomical structure in a medical image. The anatomical structure comprises a wall. The deformable model (300) is generated such that it comprises, in addition to two surface meshes (320, 360), an intermediate layer mesh (340) for being applied in-between a first surface layer of the wall and a second surface layer of the wall. In generating the intermediate layer mesh (340), the mesh topology of at least part (400) of the intermediate layer mesh is matched to the mesh topology of one of the surface meshes (320, 360), thereby establishing matching mesh topologies. The deformable model (300), as generated, better matches the composition of such walls, thereby providing a more accurate segmentation.

Abstract: The invention relates to an apparatus for determining a fractional flow reserve (FFR) value of the coronary artery system of a living being (3). A fractional flow reserve value determination unit (13) determines the FFR value by using an FFR value determination algorithm that is adapted to determine the FFR value based on a boundary condition and a provided representation of the coronary artery system, wherein the boundary condition is specific for the living being and determined by a boundary condition determination unit (12). Since the boundary condition determination unit determines a boundary condition, which is specific for the living being, and since the fractional flow reserve value determination unit not only uses the provided representation of the coronary artery system, but also the living being specific boundary condition for determining the FFR value, the accuracy of the FFR value, which is non-invasively determined, can be improved.

Abstract: The present invention relates to a device (1) for fractional flow reserve determination. The device (1) comprises a model generator (10) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor (20) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner (30) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

Abstract: Stenosis information is obtained by obtaining photographic image data (302) from a displayed image of a blood vessel (103, 203) containing the stenosis. Contours of the blood vessel and the stenosis are detected and dimensions are estimated from the photographic image data. A blood vessel model is reconstructed and fractional flow reserve data is calculated using the blood vessel model.

Abstract: A system (100) for a targeted perfusion scan includes a computed tomography (CT) scanner (120), a feeding territory map (132) and a targeted perfusion unit (140). The CT scanner (120) performs a perfusion scan of a portion of tissues of an organ. The feeding territory map (132) maps arterial locations of an arterial vessel tree to spatially located organ tissues of the organ fed by the arterial locations. The targeted perfusion unit (140) includes one or more processors (164) configured to determine targeted coverage (200) from a location of a stenosis (112, 210) and the feeding territory map, and to control the CT scanner to perform the perfusion scan according to the determined targeted coverage.

Abstract: A system (100) for segmenting a coronary artery vessel tree (182) of a patient heart in a three dimensional (3D) cardiac image (120) includes a coronary volume definition unit (150) and a coronary artery segmentation unit (180). The coronary volume definition unit (150) sets a spatial boundary (210, 220) from internal and external surfaces of heart tissues in the 3D cardiac image based on a fitted heart model (200). The coronary artery segmentation unit (180) segments the coronary artery vessel tree (182) in the 3D cardiac image using a segmentation algorithm with a search space limited by the spatial boundary set from the internal and external surfaces of the heart tissues.

Abstract: A system (IPS) and related method for fractional flow reserve, FFR, simulation. The simulation for a range of FFR values for a vasculature portion is based on a composite transfer function which is combined from a weighted sum of global effect transfer functions he, each representing a distinct physical effect that causes a pressure drop. The weights we are gotten from a previous training phase against pressure pi versus flow rate fi 5 sample measurements associated with respective vasculature geometries. The simulated range of FFR values is visualized in a graphics display (GD) as a function of pressure and flow rate values within respective intervals.

Abstract: A method of determining the blood flow through coronary arteries comprises generating (S1) a 3D image data set of at least the coronary arteries and the myocardial muscle, generating (S2) a 3D marker data set of at least the myocardial muscle from a dual-energy or spectral 3D data set obtained after administration of a marker, said 3D marker data set indicating the amount of said marker contained within voxels of said myocardial muscle, subdividing (S3) the myocardial muscle into myocardial muscle segments, determining (S4) which coronary artery supplies the respective myocardial muscle segments, determining (S5) the volume of blood that flows into the respective myocardial muscle segments from said 3D marker data set, and determining (S6) the total volume of blood that flows into a coronary artery of interest by summing the volume of blood flowing into all myocardial muscle segments supplied by said coronary artery.

Abstract: The present invention relates a segmentation apparatus (10) for interactively segmenting blood vessels (2) in angiographic image data (3). The segmentation apparatus (10) comprises a significant location determining unit (11) for determining one or more locations of a current segmentation (4) of the blood vessels (2) in the angiographic image data (3) as significant locations (5) at which the current segmentation (4) has a predetermined influence on a value of a blood flow parameter that is calculated based on the current segmentation (4), and a display unit (12) for displaying the significant locations (5) to an operator. Thereby, the operator can be guided to focus his/her segmentation efforts to those locations of the current segmentation (4) that are most relevant for the accuracy of the calculation of the value of the blood flow parameter. This may ease the burden on the operator during the segmentation procedure.

Abstract: The invention relates to a processing apparatus for processing cardiac data of a living being and to an imaging system comprising the processing apparatus. A distribution of Fractional flow reserve (FFR) values being indicative of the FFR of different coronary arteries of the living being, a distribution of myocardial perfusion values like values of an iodine map being indicative of the myocardial perfusion of different portions of the myocardium of the living being and assignments between coronary arteries and portions of the myocardium of the living being are used for determining degrees of correspondence between FFR values and myocardial perfusion values. This allows for, for example, a determination of the reliability of the FFR values, if the myocardial perfusion values are known to be reliable, based on the determined degrees of correspondence.

Abstract: Cardiac data of a living being is processed by a processing unit comprising a first fractional flow reserve (FFR) providing unit (11) for providing first FFR values being indicative of the FFR of different arteries of the living being, wherein said virtual FFR values were calculated from non-invasive imaging data of arteries of the living being; a second FFR providing unit (12) for providing FFR values measured in the arteries of the living being; a correction unit (13) configured to correct the first FFR values based on the second FFR values; and a display unit (14) configured to display at least one first FFR value and a second FFR value for a corresponding position in the coronary arteries. The first and second FFR values are displayed to a cardiologist, who can base his course of action on the simulated and corrected values.

Abstract: The invention relates to an apparatus for determining a fractional flow reserve (FFR) value of the coronary artery system of a livingbeing (3). A fractional flow reserve value determination unit (13) determines the FFR value by using an FFR value determination algorithm that is adapted to determine the FFR value based on a boundary condition and a provided representation of the coronary artery system, wherein the boundary condition is specific for the living being and determined by a boundary condition determination unit (12). Since the boundary condition determination unit determines a boundary condition, which is specific for the living being, and since the fractional flow reserve value determination unit not only uses the provided representation of the coronary artery system, but also the living being specific boundary condition for determining the FFR value, the accuracy of the FFR value, which is non-invasively determined, can be improved.

Abstract: A method is provided for generating a deformable model (300) for segmenting an anatomical structure in a medical image. The anatomical structure comprises a wall. The deformable model (300) is generated such that it comprises, in addition to two surface meshes (320, 360), an intermediate layer mesh (340) for being applied in-between a first surface layer of the wall and a second surface layer of the wall. In generating the intermediate layer mesh (340), the mesh topology of at least part (400) of the intermediate layer mesh is matched to the mesh topology of one of the surface meshes (320, 360), thereby establishing matching mesh topologies. The deformable model (300), as generated, better matches the composition of such walls, thereby providing a more accurate segmentation.

Abstract: A system (IPS) and related method for fractional flow reserve, FFR, simulation. The simulation for a range of FFR values for a vasculature portion is based on a composite transfer function which is combined from a weighted sum of global effect transfer functions he, each representing a distinct physical effect that causes a pressure drop. The weights we are gotten from a previous training phase against pressure pi versus flow rate fi 5 sample measurements associated with respective vasculature geometries. The simulated range of FFR values is visualized in a graphics display (GD) as a function of pressure and flow rate values within respective intervals.