Abstract: A method includes determining a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The method further includes registering first volumetric scan image data and second volumetric scan image data based on the registration transform. The method further includes generating registered image data. A system (100) includes a pre-scan registerer (122) that determines a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The system further includes a volume registerer (126) that registers first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data.

Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.

Abstract: A method includes obtaining 3D pre-scan image data generated from a scan of a subject. The 3D pre-scan image data includes voxels that represent a tissue of interest. The method further includes generating a 2D planning projection image showing the tissue of interest based on the 3D pre-scan image data. A system includes a 2D planning projection image from 3D pre-scan image data generator (218). The 2D planning projection image from 3D pre-scan image data generator obtains 3D pre-scan image data generated from a scan of a subject. The 3D pre-scan image data includes voxels that represent a tissue of interest. The 2D planning projection image from 3D pre-scan image data generator further generates a 2D planning projection image showing the tissue of interest based on the 3D pre-scan image data.

Abstract: A method includes obtaining first image data that includes voxel representing a structure of interest. The structure of interest includes a plurality of different sub-structures. The method further includes segmenting a volume of the first image data that includes only a single sub-structure for each of the plurality of different sub-structures. The method further includes creating a different local coordinate system for each of the different sub-structures for each of the volumes. The method further includes visually presenting the structure of interest through separate visual presentations of sets of reformatted images for each of the individual plurality of different sub-structures. A set of reformatted images for a sub-structure includes different cut planes generated from a corresponding segmented volume of the segmented volumes and the local coordinate system for the sub-structure.

Abstract: A respiratory motion determination apparatus determines respiratory motion of a living being (3). A raw data providing unit (2) provides raw data assigned to different times, wherein the raw data are indicative of a structure like the apex of the heart muscle, which is influenced by cardiac motion and by respiratory motion. A reconstruction unit (6) reconstructs intermediate images of the structure from the provided raw data. A structure detection unit (7) detects the structure in the reconstructed intermediate images. A respiratory motion determination unit (10) determines the respiratory motion of the living being based on the structure detected in the reconstructed intermediate images. This allows determining respiratory motion with high accuracy, without relying on, for example, a stable correlation between a tracking signal of an external respiratory gating device and respiratory phases.

Abstract: The invention relates to an apparatus (18) for calculating an x-ray dose distribution within an object for a computed tomography examination. A primary flux determination unit (15) determines firstly a primary flux distribution within the object, wherein then this determined primary flux distribution is used as an initial total flux distribution by a total flux determination unit (16) while applying a six-flux model algorithm. This allows the determination of the total flux distribution to start with a relatively good first approximation of the total flux distribution such that the six-flux model algorithm can determine the total flux distribution very fast. The determined total flux distribution is finally used by a dose distribution determination unit (17) for determining a total dose distribution. The apparatus allows therefore for a very fast determination of x-ray dose distributions for computed tomography examinations.

Abstract: A method for extending initial image data of a subject for dose estimation includes obtaining first image data of the subject for dose calculation, wherein the first image data has a first field of view. The method further includes obtaining second image data for extending the field of view of the first image data. The second image data has a second field of view that is larger than the first field of view. The method further includes extending the first field of view based on the second image data, producing extended image data.

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: Image processing methods and related apparatuses (SEG,UV). The apparatuses (SEG,UV) operate to utilize noise signal information in images (IM). According to one aspect, apparatus (SEG) uses the noise information (FX) to control a model based segmentation. According to a further aspect, apparatus (UV) operates, based on the noise information (FX), to visualize the uncertainty of image information that resides at edge portions of the or an image (IM).

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: The invention relates to an apparatus (18) for calculating an x-ray dose distribution within an object for a computed tomography examination. A primary flux determination unit (15) determines firstly a primary flux distribution within the object, wherein then this determined primary flux distribution is used as an initial total flux distribution by a total flux determination unit (16) while applying a six-flux model algorithm. This allows the determination of the total flux distribution to start with a relatively good first approximation of the total flux distribution such that the six-flux model algorithm can determine the total flux distribution very fast. The determined total flux distribution is finally used by a dose distribution determination unit (17) for determining a total dose distribution. The apparatus allows therefore for a very fast determination of x-ray dose distributions for computed tomography examinations.

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: Described herein is an approach to identify a presence (or absence) of a tissue disease based on a quantification of a roughness of a surface of the tissue represented in imaging data. The approach includes an image data processor (120) with a surface roughness quantifier (206) that generates a metric that quantifies a roughness of a surface of a tissue of interest in 3D image data based on a surface model adapted to the tissue of interest in the 3D image data and a decision component (208) that generates a value signal indicating a presence or an absence of disease in the tissue of interest based on the metric.

Abstract: The invention relates to a visualization apparatus (1) for visualizing an image data set. The visualization apparatus (1) comprises an image data set providing unit (2) for providing the image data set, a differential property determination unit (5) for determining local differential properties for different regions of the image data set, an assigning unit (6) for assigning visualization properties to the different regions of the image data set depending on the determined local differential properties, wherein a visualization property defines the visualization of a region, to which the visualization property is assigned, and a display unit (7) for displaying the visualization properties assigned to the different regions of the image data set. By displaying the visualization properties assigned to the different regions of the image data set different objects can visually be separated from each other without requiring large computational costs.

Abstract: A system and method are provided for guiding surgery using MR images and radioactive markers. The method comprises reconstructing the surface of an anatomical structure and a gamma probe orientated to optimize a radioactivity reading from a radioactive seed placed at a target location in the anatomic structure for each of one or more positions of the gamma probe. The position and orientation of the gamma probe is detected in each reconstructed surface to estimate a position of the radioactive seed relative to the reconstructed surface.

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: 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: A double focal spot X-ray tube (104) is used to acquire a set of two images PI?, PI? for a given gantry position from slightly different view positions. The stereo or binocular disparity (BD) of imaged structures is used to estimate the object depth in view direction, which in turn is used to discriminate between objects inside IO and outside EO the body. Respective structures are virtually removed from the images PI?, PI?.

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.