Abstract: A method is disclosed for identification of a contrasted blood vessel in digital 3D image data, the method using a generic region-growing algorithm with several steps, for which among other things seed points are searched for and, in dependence on a current threshold value, are assigned to corresponding seed point sets. The number of seed points which are associated during a specific section of the method to the same seed point set with the threshold value is recorded and a leakage signal is produced if the number exceeds a maximum value. When the leakage signal occurs, those seed points which have been associated with the threshold value during that section are not stored as vessel voxels, the method is terminated at the location of the leakage and the remaining method is continued.

Abstract: A method is disclosed for segmenting anatomical structures, in particular the coronary vessel tree, from 3D image data. In the method, a starting point is initially set in the 3D image data, and at least one known anatomically significant point and/or at least one known anatomically significant surface are/is identified in the 3D image data. Subsequently, proceeding from the starting point the structure is subsequently segmented pixel by pixel with the aid of a multiplicity of segmentation steps in such a way that an instantaneous distance is determined automatically relative to the anatomically significant point and/or to the anatomically significant surface in each segmentation step. Further, segmentation parameters and/or a selection of adjacent pixels for continuing the segmentation are/is established as a function of the distance, taking account of a model topology. The method enables an accurate and reliable segmentation of the anatomical structure.

Abstract: A method is disclosed for actuating an image output device for the output of slice images, obtained from volume data, of a tissue region including at least one hollow organ section. In at least one embodiment, tangential slice planes at observation points along at least one profile line section through the hollow organ section are determined on the basis of provided volume data. In the process, the profile line section is decomposed into shorter profile line sections such that the generated profile line sections are each situated at least approximately in a plane assigned to the respective profile line section as per a predetermined quality criterion. First tangential slice planes are each assigned to the possible observation points on the associated profile line sections on the basis of these planes.

Abstract: A method is disclosed for automatically determining the position and orientation of the left ventricle and/or adjacent regions in 3D image data records of the heart that have been recorded with the aid of an imaging, tomographic method after injection of contrast agent. In the method, the left ventricle is firstly coarsely segmented, and the long main axis is determined from the segmented image data. Starting from this long main axis, end points of a boundary line of the septum are determined in a plane by using search beams. The segmented image data, the long main axis and the end points fix the position and orientation of the left ventricle in the image data record.

Abstract: A method is disclosed for visualizing bumps of the inner surface of a hollow organ. In at least one embodiment, the method includes acquiring recorded image data of the hollow organ using an imaging system; drawing a cutting edge in the image data along the surface of the hollow organ in the longitudinal direction; preparing the image data to display the surface of the hollow organ along a plane on which the surface is plotted in an opened-up fashion; and changing a viewing angle and/or an illumination angle during a display of the hollow organ, a rotation of the plane along an axis running parallel to the cutting edge and/or along an axis running transversely to the cutting edge being carried out to change the viewing angle. A visualization module, an image processing device with such a visualization module and a tomographic system with such an image processing system.

Abstract: A method and apparatus for detecting 3D anatomical objects in medical images using constrained marginal space learning (MSL) is disclosed. A constrained search range is determined for an input medical image volume based on training data. A first trained classifier is used to detect position candidates in the constrained search range. Position-orientation hypotheses are generated from the position candidates using orientation examples in the training data. A second trained classifier is used to detect position-orientation candidates from the position-orientation hypotheses. Similarity transformation hypotheses are generated from the position-orientation candidates based on scale examples in the training data. A third trained classifier is used to detect similarity transformation candidates from the similarity transformation hypotheses, and the similarity transformation candidates define the position, translation, and scale of the 3D anatomic object in the medical image volume.

Abstract: A method and an apparatus are disclosed for visualizing tubular anatomical structures, in particular vessel structures, in medical 3D image records.

Abstract: A method is disclosed for visualizing tubular anatomical structures, in particular vessel structures, in medical 3D image records. In at least one embodiment, the method includes the following: firstly, providing 3D image data of the tubular anatomical structure; secondly, displaying a first image of the tubular anatomical structure on the basis of the 3D image data; thirdly, selecting an image voxel which is assigned to the tubular structure in the 3D image data on the basis of the first image; fourthly, determining a centerline of the tubular anatomical structure in a prescribably delimited region of the 3D image data comprising the image voxel; fifthly, selecting a point of the centerline; sixthly, generating one or more 2D slice images assigned to the point, the 2D slice images in each case representing a sectional plane in the 3D image data; and seventhly, displaying the 2D slice images.

Abstract: A method is disclosed for visualizing tubular anatomical structures from 3D recorded medical images, in particular coronary vessel structures, in the case of which segmented 3D image data of the tubular structure are firstly provided. The tubular structure represented by the segmented 3D image data is approximated via a multiplicity of mutually adjacent cylindrical and/or conically tapering elements. The mutually adjacent elements are subsequently displayed without the segmented 3D image data of the tubular structure. The method enables a simplified geometric display of the tubular structure that enables the person skilled in the art to make a simple interpretation of the structure, particularly in the case of transmission as a 2D image display.

Abstract: A method and an apparatus are disclosed for visualizing deposits in blood vessels, particularly in coronary vessels. In such a method, 2D slice images may be reconstructed from the measurement data, with image data of the 2D slice images being post-processed for local determination of brightness values and/or of default values on which these are based in the 2D slice images. In the presentation of the 2D slice images, one or more image areas are marked in which, in the post-processing, pixels are automatically color-coded and presented according to a predeterminable transfer function which assigns different colors to different value ranges of brightness values and/or of default values on which these are based.

Abstract: A system and method for colon unfolding via skeletal subspace deformation comprises: performing a centerline computation on a segmented image for deriving a centerline thereof; computing a distance map utilizing said centerline and said segmented image to derive said distance map; generating a polyhedral model of the lumen of said colon; and utilizing said polyhedral model, said distance map, and said centerline for performing a straightening operation on said centerline.

Abstract: A method and system for automatically associating coronary arteries with regions of the myocardium to which the arteries supply blood is described. The method uses three dimensional image data of a patient, and an axial image slice is used to identify candidate locations of the aorta. Candidate aorta centroid locations are evaluated to eliminate spurious identifications, and the identified aorta is used to locate the left ventricle of the heart with respect thereto. Arteries of the coronary artery tree may be located by segmentation of contrasted images, and the individual arteries may be identified by skeletonization of the segmented arteries. The skeletonized arteries are projected onto an image of the patient heart, and may be associated with specific regions of the myocardium.

Abstract: A method and system for left ventricle (LV) endocardium surface segmentation using constrained optimal mesh smoothing is disclosed. The LV endocardium surface in the 3D cardiac volume is initially segmented in a 3D cardiac volume, such as a CT volume, resulting in an LV endocardium surface mesh. A smoothed LV endocardium surface mesh is generated by smoothing the LV endocardium surface mesh using constrained optimal mesh smoothing. The constrained optimal mesh smoothing determines an optimal adjustment for each point on the LV endocardium surface mesh by minimizing an objective function based at least on a smoothness measure, subject to a constraint bounding the adjustment for each point. The adjustment for each point can be constrained to prevent adjustments inward toward the blood pool in order to ensure that the smoothed LV endocardium surface mesh encloses the entire blood pool.

Abstract: A method and system for modeling the aortic valve in 4D image data, such as 4D CT and echocardiography, is disclosed. An initial estimate of a physiological aortic valve model is determined for at least one reference frame of a 4D image sequence based on anatomic features in the reference frame. The initial estimate is refined to generate a final estimate in the reference frame. A dynamic model of the aortic valve is then generated by estimating the physiological aortic valve model for each remaining frame of the 4D image sequence based on the final estimate in the reference frame. The aortic valve can be quantitatively evaluated using the dynamic model.

Abstract: In an image post-processing method and apparatus for 3D visualization of 2D/3D fused image data for use in catheter angiography in an endovascular interventional procedure, upon forward movement of a micro-catheter through blood vessel in the interventional procedure, x-ray images are acquired from different projection directions and are subjected to a pattern recognition algorithm for edge-based segmentation of the image regions filled by the micro-catheter, with all remaining image regions being masked out. The segmented projection exposures are prepared by a 3D reconstruction algorithm to obtain an image data set for (pseudo-) three-dimensional representation of the micro-catheter. This image data set are intraoperatively registered and fused with an image data set acquired from an angiographic pre-examination for three-dimensional visualization of the vessel topography.

Abstract: A method and system for measuring the volume of the left ventricle (LV) in a 3D medical image, such as a CT, volume is disclosed. Heart chambers are segmented in the CT volume, including at least the LV endocardium and the LV epicardium. An optimal threshold value is automatically determined based on voxel intensities within the LV endocardium and voxel intensities between the LV endocardium and the LV epicardium. Voxels within the LV endocardium are labeled as blood pool voxels or papillary muscle voxels based on the optimal threshold value. The LV volume can be measured excluding the papillary muscles based on the number of blood pool voxels, and the LV volume can be measured including the papillary muscles based on the total number of voxels within the LV endocardium.

Abstract: A method and a workstation are disclosed for visualizing a three-dimensional image data record having a multiplicity of voxels of a heart of a patient, recorded with the aid of an x-ray CT examination carried out with contrast agent present in the bloodstream. In at least one embodiment, the method includes saving the CT image data record including a multiplicity of voxels defined by absorption values, determining the voxels associated with the chamber of the heart by segmenting the chambers of the heart filled with blood containing the contrast agent, removing the image information from the voxels associated with the chambers of the heart, calculating a two-dimensional virtual projection from the remaining CT image data record, and displaying the virtual two-dimensional projection.

Abstract: A method is for automatic object marking in medical imaging. The method includes coupled displaying of different display modes of at least one image data record containing at least one object to be marked, in different display windows on at least one computer screen. The method further includes transferring the position of an initial point, selected by the user as part of an object-determining first marking, to the computer. Then, pattern recognition techniques are applied to the environment of the initial point of the first marking, resulting in a detailed high-resolution second marking of the object. Thereafter, reversible coding of the second marking of the image data records present in the computer takes place. Finally, the marked object is accentuated relative to its environment in the image data records on the screen.

Abstract: A method and system for building a statistical four-chamber heart model from 3D volumes is disclosed. In order to generate the four-chamber heart model, each chamber is modeled using an open mesh, with holes at the valves. Based on the image data in one or more 3D volumes, meshes are generated and edited for the left ventricle (LV), left atrium (LA), right ventricle (RV), and right atrium (RA). Resampling to enforce point correspondence is performed during mesh editing. Important anatomic landmarks in the heart are explicitly represented in the four-chamber heart model of the present invention.

Abstract: A method is disclosed for the segmented representation of vessel-like structures of an object under examination, on the basis of tomographic data, wherein a three-dimensional tomographic volume data record of the object under examination is generated and a segmentation is carried out which enhances the vessel-like structures in the representation of the tomographic data. According to an embodiment of the invention, for each voxel, the probability with which the voxel is located in a vessel structure is determined from the environmental data of the voxel with the aid of a vessel-specific filter of a spatial dimension which corresponds to the tomographic volume data record, on the basis of Gaussian functions, and these determined probabilities are additionally used as criterion for the presence of a vessel in the segmentation process for the representation of vessel structures.