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 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 function of the modified transformed vessel model, wherein the objective function comprises a location-prior term based on a localization of the modified transformed vessel model relative to the transformed joined model. Hence, the system is arranged to model a vessel taking into account the localization of a vessel model relative to a reference anatomical structure described by a reference model.
Abstract:
A data structure for use by a computer system for comparing temporally varying medical data (9a, 9b) is disclosed. The data structure performs the steps of receiving a first data set (9a) including first data representing a medical parameter at a plurality of first times, receiving a second data set (9b) including second data representing said medical parameter at a plurality of second times, and processing said first and/or second data sets to increase a degree of correlation or similarity between a plurality of said first and second times representing identifiable events.
Abstract:
A patient data record is described comprising a mean model representative of the patient and further comprises at least one shape model to represent data concerning the patient, in which the said mean model comprises at least one region and the said shape model comprises at least one sub-section, and in which the at least one sub-section of the shape model is linked to the equivalent region of the mean model. This has the advantage of allowing greater structure to the patient record. Further a system is described to present patient data upon queries generated by a user and arranged to access the claimed patient data record, and which is further arranged to provide access to information in the sub-section of the shape model when a query generated by the user accesses the equivalent region of the mean model. This system allows full use of the improved patient data record.
Abstract:
A method and apparatus for interactively manipulating a shape of an object, comprising selecting an object to be manipulated and rendering the object in dependence of a manipulation type. The method provides a smart object adapted interaction, manipulation and visualization scheme in contrast to previous display driven schemes. The method allows efficient shape manipulation by restricting the degrees of freedom for the manipulation to the meaningful ones for a given object or object part, thus allowing to reduce e.g. a 3D interaction to a 2D interaction.
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:
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:
The invention relates to a method of segmenting a surface in a multi dimensional dataset comprising a plurality of images. In accordance with the method of the invention, at step 4 shape parameters and topology parameters for the object under consideration are acquired. Preferably that the multi-dimensional data set imaging the object is acquired at an acquisition step 1 and is subsequently stored in a computer-readable file 2. At step 5 the default shape parameters and topology parameters of a suitable segmentation algorithm 3 based on a deformable model are adapted with the value of the actual shape parameters and the topology parameters 4 for the given object. Subsequently, at step 6 the images constituting the multi-dimensional dataset are segmented using deformable model algorithm 6a with the adapted shape parameters and the adapted topology parameters yielding respective portions of the sought surface. After all sub-portions of the segmented surface are obtained for all images, the surface is tracked using per se known tracking algorithms 8a resulting in establishing spatial correspondence between said surface portions. Preferably, the method according to the invention is followed by the step of reconstructing 9 wherein for a given viewing angle the surface is reconstructed in virtual space. At step 11 the reconstructed surface is visualized on a suitable display means for user's analysis.
Abstract:
The invention relates to a device and a process, with which images of different imaging methods can be registered, for example preoperatively obtained 3D X-ray images (A) and intra operatively obtained ultrasound images (B). First transformed images (A',B') are then generated in a data processing device (10), which are aligned to each other with regard to the peculiarities of each imaging method. Particularly from the three dimensional CT-image (A), can be generated a two dimensional image (A') which adheres to the characteristic means of representation of an ultrasound system, while shaded areas behind bones and/or gas-filled volumes can be blended out. With a feature-based registration of the transformed images (A', B') errors are avoided, which are traced back to artifacts and peculiarities of the respective imaging methods.