Abstract: A method for reformatting image data includes obtaining volumetric image data indicative of an anatomical structure of interest, identifying a surface of interest of the anatomical structure of interest in the volumetric image data, identifying a thickness for a sub-volume of interest of the volumetric image data, shaping the sub-volume of interest such that at least one of its sides follows the surface of interest, and generating, via a processor, a maximum intensity projection (MIP) or direct volume rendering (DVR) based on the identified surface of interest and the shaped sub-volume of interest.

Abstract: A system (100) for segmenting an object in an image adapts a first model for segmenting the object to the image. A feature is extracted from the image based on the adapted first model. A second model is selected for segmenting the object from a plurality of models for segmenting the object, based on the feature extracted from the image. The second model includes additional detail of the object. The second model is utilized based on the adapted first model and/or the feature extracted from the image; the initialized second model is adapted to the image. The features extracted from the image based on the adapted first model help the system (100) to select the second model for segmenting the object from a plurality of models for segmenting the object. The adapted first model and/or the extracted features are also used for initializing the second model.

Abstract: An processor (118) includes a bullous emphysema identifier (206) that processes voxels of the volumetric image data and identifies voxels corresponding to bullous emphysema, a two dimensional projection image generator (206) that generates a 2D bullous emphysema projection image based on the voxels corresponding to bullous emphysema, wherein an intensity of a contour of a bulla in the 2D bullous emphysema projection image is based on a size of the bulla, and a feature highlighter (210) that highlights the bullous emphysema in the 2D bullous emphysema projection image using second first indicia.

Abstract: The present invention relates to a method for segmenting MR Dixon image data. A processor and a computer program product are also disclosed for use in connection with the method. The invention finds application in the MR imaging field in general and more specifically may be used in the generation of an attenuation map to correct for attenuation by cortical bone during the reconstruction of PET images. In the method, a surface mesh is adapted to a region of interest by: for each mesh element in the surface mesh: selecting a water target position based on a water image feature response in the MR Dixon water image; selecting a fat target position based on a fat image feature response in the MR Dixon fat image; and displacing each mesh element from its current position to a new position based on both its water target position and its corresponding fat target position.

Abstract: A medical system includes a medical instrument (102) configured for interventional deployment and a shape sensing system (104) mounted on or in the medical instrument and configured to measure a shape of the medical instrument during the interventional deployment. An imaging device (106) is mounted on or in the medical instrument and configured to image a lumen in which the imaging device is deployed. A registration module (140) is configured to register the shape of the medical instrument to an image of the lumen at a particular time to reconstruct a three-dimensional geometry of the lumen, accounting for motion.

Abstract: A method includes displaying a background image on a display screen. The method further includes receiving, from an input device, a signal indicative of a free hand line being drawn over the background image. The signal includes coordinates of points of the free hand line with respect to the display screen. The free hand line is independent of content represented in the background image. The method further includes storing the signal in a storage device. The method further includes generating a smooth stiff line based on the stored signal. The method further includes displaying the smooth stiff line over the background image.

Abstract: A method includes performing a motion compensated reconstruction of functional projection data using a patient-adapted motion model, which is generated based on a generic anatomical motion model and imaging data from a structural scan. A system includes a first adapter (202) configured to adapt a generic anatomical model to structural image data, producing an adapted model, a forward projector (204) configured to forward project the adapted model, producing forward projected data, and a second adapter (206) configured to adapt the forward projected data to individual projections of projected data, which is used to generate the structural image data, producing a patient-adapted motion model.

Abstract: A method includes determining a change in a volume of a tissue of interest located in at least two data sets between the at least two data sets. The at least two image data sets include a first image data set acquired at a first time and a second image data set acquired at a second time, and the first and second times are different. The method includes generating a rendering which includes a region in which the tissue of interest is located and indicia that indicates a magnitude of the change across the region. The region is superimposed over the rendering, which is generated based on at least one of the at least two image data sets, and linked to a corresponding image respectively in the at least two image data sets including voxels representing tissue of interest. The method includes visually presenting the rendering in a graphical user interface.

Abstract: A system for validating motion estimation comprising a field unit (110) for obtaining a deformation vector field (DVF) estimating the motion by transforming a first image at a first phase of the motion into a second image at a second phase of the motion, a metric unit (120) for computing a metric of a local volume change at a plurality of locations, and a conformity unit (130) for computing a conformity measure based on the computed metric of the local volume change at the plurality of locations and a local property of the first or second image defined at the plurality of locations. Based on the value of the conformity measure, the DFV estimating the motion is validated. Experiments show that the conformity measure based on the computed metric of a local volume change at a plurality of locations and the local property of the first or second image, defined at the plurality of locations, does not necessarily favor a large weight for the outer force to provide a more accurate registration.

Abstract: The present invention relates to an image processing device for detecting line structures in an image data set. The device comprises a model definition unit (12) for defining a line model of a line structure to be detected, said line model comprising a number of voxels, a calculation unit (14) for calculating, per voxel of interest of said image data set, several correlation values of a correlation between said line model and an image area around said voxel of interest, said image area comprising a corresponding number of voxels as said line model, wherein for each of a number of different relative orientations of said line model with respect to said image area a respective correlation value is calculated, and a determining unit (16) for determining, per voxel of interest, the maximum correlation value from said calculated correlation values and the corresponding optimal orientation at which said maximum correlation value is obtained.

Abstract: An imaging system (10) analyzes airways of a patient. The system (10) includes a hardware phantom (50) including tubes (54) representative of airways. The tubes (54) include different lumen sizes and/or wall thicknesses. The system further includes an imaging scanner (12) for scanning a region of interest (ROI), including the airways, and the hardware phantom (50) to create raw image data. At least one processor (32) is programmed to at least one of: (1) correct measurements of walls of the airways based on measurements of lumen size and/or wall thickness of the tubes (54) and known lumen size and/or wall thickness of the tubes (54); and (2) generate an image of the ROI in which color and/or opacity of the airways are based on a comparison of images or maps of the tubes (54) and images or maps of the airways. A corresponding method is also provided.

Abstract: An image registration apparatus (118) includes an image quality driven image registration determiner (202) that determines an image quality driven image registration for a set of images to register based on a non-rigid registration (204), which includes an optimization of an image similarity term and a regularization term, and a registration steering factor, and a registration component (206) that registers the set of images using the image quality driven image registration. A method determining an image quality driven image registration for a set of images to register based on a non-rigid registration, which includes an optimization of an image similarity term and a regularization term, and a registration steering factor, and registering the set of images using the fidelity driven image registration, generating a set of registered images.

Abstract: An object motion parameter determiner (122) includes a deformation vector field determiner (210) that determines deformation vector fields for a 4D image set, which includes three or more images corresponding to three or more different motion phases of motion of a moving object. The object motion parameter determiner further includes a volume curve determiner (212) that generates a volume curve for the voxel based on the deformation vector fields. The object motion parameter determiner further includes a model fitter (214) that fits a predetermined motion model to the volume curve. The object motion parameter determiner further includes a parameter determiner (218) that estimates at least one object motion parameter based on the fitted model.

Abstract: The present invention relates to devices, system and method for detecting gestures. The devices, systems and methods uses optically shape sensing devices for tracking and monitoring users. This allows unhindered, robust tracking of persons in different setting. The devices, systems and methods are especially useful in health care institutions.

Abstract: A voxel tagging system (100) includes a sensing enabled device (104) having an optical fiber (126) configured to sense induced strain within the device (Bragg grating sensor). An interpretation module (112) is configured to receive signals from the optical fiber interacting with an internal organ, e.g. heart, and to interpret the signals to determine positions visited by the at least one optical fiber within the internal organ. A data source (152, 154) is configured to generate data associated with an event or status, e.g. respiration, ECG phase, time stamp, etc.. A storage device (116) is configured to store a history (136) of the positions visited in the internal organ and associate the positions with the data generated by the data source (152, 154).

Abstract: A method image data processor (318) includes a shape likelihood determiner (402) that processes voxels of image data and determines a likelihood that a voxel represents predetermined tissue of interest for a plurality of the voxels based on a shape of a tissue represented by the voxel, an opacity determiner (406) that determines an opacity suppression for each of the plurality of voxels based on the likelihood, a re-formatter (410) that re-formats the image data based on the determined opacity suppression, generating opacity suppressed re-formatted data, and a rendering engine (412) that visually presents the opacity suppressed re-formatted data.

Abstract: A system for visualizing an object in image data using a first cross-section surface coupled to a model of the object, the system comprising a model unit for adapting a model to the object in the image data, a surface unit for adapting the first cross-section surface to the adapted model on the basis of the coupling between the first cross-section surface and the model, and a visualization unit for computing an image from the image data on the basis of the adapted first cross-section surface. The first cross-section surface may be used to define a slice of the image data for visualizing useful features of the object. Advantageously, adapting the model to the object in the image data and the coupling between the first cross-section surface and the model enable the first cross-section surface to be adapted to the image data. Thus, the shape, orientation and/or position of the adapted first cross-section surface is/are based on the shape, orientation and/or position of the adapted model.

Abstract: An processor (118) includes a bullous emphysema identifier (206) that processes voxels of the volumetric image data and identifies voxels corresponding to bullous emphysema, a two dimensional projection image generator (206) that generates a 2D bullous emphysema projection image based on the voxels corresponding to bullous emphysema, wherein an intensity of a contour of a bulla in the 2D bullous emphysema projection image is based on a size of the bulla, and a feature highlighter (210) that highlights the bullous emphysema in the 2D bullous emphysema projection image using second first indicia.

Abstract: The invention relates to a system for segmenting an object in image data using model-based image segmentation. The system comprises a feature unit for identifying features in the image data for computing an external energy of a mesh on the basis of a current position of the mesh. The feature unit further comprises a candidate feature unit for selecting a plurality of candidate features in the image data. The feature unit further comprises a position unit for determining a position of each candidate feature of the plurality of the candidate features relative to a region of the image data. The feature unit further comprises a feature function unit for computing a strength of each candidate feature. The feature unit further comprises an evaluation unit for evaluating each candidate feature of the plurality of candidate features and for identifying the feature among the plurality of candidate features based on this evaluation.

Abstract: A planning tool, system and method include a processor (114) and memory (116) coupled to the processor which stores a planning module (144). A user interface (120) is coupled to the processor and configured to permit a user to select a path through a pathway system (148). The planning module is configured to upload one or more slices of an image volume (111) corresponding to a user-controlled cursor point (108) guided using the user interface such that as the path is navigated the one or more slices are updated in accordance with a depth of the cursor point in the path.