Abstract: The invention relates to a system (100) 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. Any suitable rendering technique, e.g. maximum intensity projection, can be used by the visualization unit to compute the image based on the slice of the image data defined by the first cross-section surface.

Abstract: The invention relates to a system (100) for producing a representation of an object in image data, based on a template coupled to a model of the object, the system comprising a model unit for adapting the model to the object in the image data, and a template unit for adapting the template to the adapted model on the basis of the coupling between the template and the model. The template defines a representation of the object which is simpler to interpret than the model. The template may be arranged to emphasize useful features of the object. The template comprises substantially fewer degrees of freedom and thus can be efficiently adapted to the model. Because the template of the invention is coupled to the model, the position, orientation and/or shape of the template is determined by the model adapted to the object in the image data. Hence, the template is adapted to the image data. The adapted template is capable of representing the object and its individual characteristics, e.g.

Abstract: An automated method (1) for the automatic extraction of a pulmonary vessel tree from a 3D medical image, such as multi-slice CT data, is disclosed. A segmented pulmonary vessel is identified as either an artery or a vein by determining a measure for arterialness for the vessel. The measure is based on a relation of the orientation of a local bronchus to the orientation of the segmented pulmonary vessel of the local bronchus. When a vessel is identified as a pulmonary artery, it is added to the pulmonary artery tree. Radii of the pulmonary artery and bronchus are measured automatically and positions where a ratio of these radii exhibits unusual values are presented in a display, preferably for suggesting further assessment by a radiologist, which for instance is useful for pulmonary embolism detection.

Abstract: The present invention relates to an image processing device and a corresponding image processing method for processing a multi-dimensional data set of image data, in particular of three-dimensional medical volume image data, including a segmentation unit (6, 16, 26) for a segmentation of an image object in said data set. Further, the present invention relates to a computer program for implementing said image processing method on a computer.

Abstract: The invention relates to a system (100) for segmenting a plurality of objects in image data using simultaneous model-based image segmentation. A surface mesh is adapted to each object to be segmented. To avoid or reduce the possibility of mesh collision, a plurality of connecting edges for connecting two proximal meshes are used. A connection energy defined for the plurality of connecting edges allows controlling the spatial relationship between the first and second mesh. This is achieved by including in the connection energy expression terms that will increase the connection energy when the lengths of edges of the plurality of connecting edges connecting the first and second mesh decrease. Using the reference configuration of the plurality of connecting edges defined based on the pre-positioned first and second mesh allows taking into account prior knowledge about a typical spatial relationship between the first and second object of the plurality of objects.

Abstract: The present invention relates to an apparatus (1) for segmenting an object comprising sub-objects shown in an object image. The apparatus comprises a feature image generation unit (2) for generating a feature image showing features related to intermediate regions between the sub-objects and a segmentation unit (3) for segmenting the sub-objects by using the object image and the feature image. Preferentially, the feature image generation unit (2) is adapted for generating a feature image from the object image. In a further embodiment, the feature image generation unit (2) comprises a feature enhancing unit for enhancing features related to intermediate regions between the sub-objects in the object image.

Abstract: The invention relates to a system (100) for segmenting an object in image data using model-based image segmentation, the system comprising a feature unit (120) 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, wherein the feature unit (120) further comprises a candidate feature unit (122) for selecting a plurality of candidate features in the image data, for identifying a feature to be included in the features identified in the image data, a position unit (124) for determining a position of each candidate feature of the plurality of the candidate features relative to a region of the image data, a feature function unit (126) for computing a strength of each candidate feature, wherein the strength of each candidate feature depends on the position of each candidate feature relative to the region, and an evaluation unit (128) for evaluating each candidate feature of the plurality of candidate features and for identifying the featu

Abstract: The system 10 comprises an input 2 for accessing the suitable input data. The core of the system 10 is formed by a processor 4 which is arranged to operate the components of the system 10, it being the input 2, a computing unit 5, a working memory 6. The computing unit 5 preferably comprises a suitable number of executable subroutines 5a, 5b, 5c, 5d, 5e, and 5f to enable a constructing of a geometric model of the movable body based on the results of the segmentation step, finding a spatial correspondence between the first and second image dataset, mapping the texture image dataset on geometric model, fusing the geometric model and the mapped texture image dataset. The apparatus 10 according to the invention further comprises a coder 7 arranged to code the determined region of interest in accordance to a pre-selected criterion. The criterion may be selectable from a list of valid criteria, stored in a file 7a.

Abstract: The present invention relates to a method for performing computer-aided detection (CAD) of a disease, e.g. lung tumours, on a medical image data set (20) from a imaging modality, such as MRI or CT. Initially, there is perform a segmentation of the medical image data set (20) using an anatomical model. Secondly, the segmented data is analyzed for characteristics of the disease resulting in a set of analysis data (25), and finally the set of analysis data (25) is evaluating with respect to the disease. At least one of these steps comprises as an input a position dependent probability (P_r) for the disease. The invention is advantageous in that more efficient computations can be performed because the degree of analysis in a certain region of the part of the patient, e.g. the lung, can be adjusted or tailored to the level of probability of the disease in the that region.

Abstract: The semi-automatic extraction and delineation of the cardiac region of interest in computer tomographic angiography images is time consuming and requires an experienced operator. According to the present invention, a completely automatic delineation and extraction of the CROI is provided, wherein the chest wall is detected and the region where the CROI is attached to the chest wall. Then, the descending aorta is detected. After that a circular initialization of a closed contour around a part of the CROI is performed, which is optimized in a subsequent step. Then, a propagation is performed through all slices of the CTA image, where the preceding contour of the preceding slice image is used for an actual contour optimization in the actual slice image. Advantageously, a fully automatic delineation and extraction of the CROI is provided within very short time.

Abstract: An automated method (1) for the automatic extraction of a pulmonary vessel tree from a 3D medical image, such as multi-slice CT data, is disclosed. A segmented pulmonary vessel is identified as either an artery or a vein by determining a measure for arterialness for the vessel. The measure is based on a relation of the orientation of a local bronchus to the orientation of the segmented pulmonary vessel of the local bronchus. When a vessel is identified as a pulmonary artery, it is added to the pulmonary artery tree. Radii of the pulmonary artery and bronchus are measured automatically and positions where a ratio of these radii exhibits unusual values are presented in a display, preferably for suggesting further assessment by a radiologist, which for instance is useful for pulmonary embolism detection.

Abstract: The invention relates to a system (100) for registering a vessel model with an image data set based on a joined model comprising a reference object model and the vessel model, the system comprising: a placement unit (110) for placing the joined model in a space of the image data set, thereby creating a placed joined model comprising a placed reference object model and a placed vessel model; a computation unit (120) for computing a deformation field based on a landmark displacement field comprising displacements of landmarks of the placed reference object model relative to corresponding landmarks in the image data set; a transformation unit (130) for transforming the placed joined model using the deformation field, thereby creating a transformed joined model comprising a transformed reference object model and a transformed vessel model; and a registration unit (140) for registering the transformed vessel model with the image data set based on modifying the transformed vessel model and optimizing an objective f

Abstract: The invention relates to a system (100) for adapting a plurality of model meshes to a plurality of image data, the system comprising a registration unit (110) for registering the plurality of model meshes with the plurality of image data on the basis of a computation of a registration transformation for transforming the plurality of model meshes, and an adaptation unit (120) for adapting the plurality of registered model meshes to the plurality of image data on the basis of a computation of locations of mesh vertices of the plurality of model meshes.

Abstract: Modeling of organ surfaces is a well-established method that may serve in computer-supported teaching, but also in image-based medical diagnosis and in clinical interventions. According to an exemplary embodiment of the present invention, a method of constructing a multi-surface model from a multi-dimensional dataset of an object of interest is provided, which combines single basic two-dimensional manifold surface meshes, resulting in a multi-surface model. According to an aspect of the present invention, this resulting model may be a non-two-dimensional manifold mesh.

Abstract: The invention relates to a system (100) for propagating a model mesh based on a first mean model mesh and on a second mean model mesh, the system comprising: a registration unit (110) for computing a registration transformation for registering the first model mesh with the first mean model mesh; a forward transformation unit (120) for transforming the model mesh into a registered model mesh using the registration transformation; a computation unit (130) for computing a propagation field for propagating the registered model mesh, the propagation field comprising vectors of displacements of vertices of the second mean model mesh relative to respective vertices of the first mean model mesh; a propagation unit (140) for transforming the registered model mesh into the propagated registered model mesh based on applying the vertex displacement vectors comprised in the propagation field to respective vertices of the registered model mesh; and an inverse transformation unit (150) for transforming the propagated regist

Abstract: The system 10 comprises an input 2 for accessing the suitable input data. The core of the system 10 is formed by a processor 4 which is arranged to operate the components of the system 10, it being the input 2, a computing unit 5, a working memory 6. The computing unit 5 preferably comprises a suitable number of executable subroutines 5a, 5b, 5c, 5d, 5e, and 5f to enable a constructing of a geometric model of the movable body based on the results of the segmentation step, finding a spatial correspondence between the first and second image dataset, mapping the texture image dataset on geometric model, fusing the geometric model and the mapped texture image dataset. The apparatus 10 according to the invention further comprises a coder 7 arranged to code the determined region of interest in accordance to a pre-selected criterion. The criterion may be selectable from a list of valid criteria, stored in a file 7a.

Abstract: The invention relates to a method for the interactive segmentation of a structure contained in an object from a three-dimensional image of the object. In an expansion mode a region expansion process is carried out, the results of said process simply being completely or partly undone again in a contraction mode. A quasi-continuous similarity measure can be used to determine whether or not a voxel belongs to the structure to be segmented. The expansion taking place in the region expansion process always involves the voxels having the largest similarity measure each time.

Abstract: The invention relates to a method (100) of and to a system (200) for determining a template mesh of a shape model on the basis of a plurality of instances of the shape model. The method of determining the template mesh of the shape model comprises an obtaining step (110) for obtaining the plurality of instances of the template mesh, a computing step (120) for computing a plurality of results on the basis of the plurality of instances of the shape model, a deciding step (130) for deriving a decision on the basis of the plurality of results, and a decimating step (140) for decimating the template mesh of the shape model on the basis of the decision, thereby determining the template mesh of the shape model. Thus, the template mesh of the shape model determined by the method of the invention better describes objects of interest at all locations.

Abstract: A reconstruction unit is provided for receiving a sequence of data sets, the data sets representing structural information of the object. The reconstruction unit performs receiving scheduling information related to the data sets of the sequence of data sets. Then reconstructing a sequence of coarse reconstructions of the object by using the sequence of data sets and the scheduling information. Afterwards a sequence of adapted models of the object is generated by adapting a respective model to each of the coarse reconstructions. Then a motion of a predetermined portion of each of the adapted models is determined and a specific data set of the sequence of data sets is selected, wherein the specific data set corresponds to the adapted model with the minimum motion of the predetermined portion. Finally the reconstruction unit performs reconstructing a fine reconstruction of at least the part of the object using the specific data set.

Abstract: An imaging method for identifying abnormal tissue in the lung is provided, comprising the recording of slice images of the lung by means of X-ray radiation, recording of blood vessels, differentiation of blood vessels and abnormal tissue, segmentation of the abnormal tissue and display of the segmented abnormal tissue on an output device. In addition, a computer tomograph for identifying abnormal tissue in the lung is provided, having a radiation source for recording slice images of the lung and blood vessels by means of X-ray radiation, a computer unit for differentiating the blood vessels from the abnormal tissue and for segmenting the abnormal tissue, as well as an output device for displaying the segmented abnormal tissue.