Abstract: A system and method are provided for volume rendering of image data of an image volume. A segmentation model is applied to the image data of the image volume, thereby delineating a sub-volume of the image volume. The image data inside the sub-volume is volume rendered. A user interface is provided which enables a user to interactively adjust the sub-volume by applying at least one of: a push action and a pull action to the sub-volume. The push action may cause part of the sub-volume to be pulled inwards, whereas the pull action may cause part of the sub-volume to be pulled outwards. The volume rendering of the sub-volume may be updated in response to a user's adjustment of the sub-volume.

Abstract: There is provided a method and apparatus for adjusting a model of an anatomical structure in a sequence of images of the anatomical structure. The model is placed with respect to the anatomical structure in the sequence of images. A user input is received to adjust the model in a selected image of the sequence, and based on the user input, a part of the model that lies in the selected image and a previously unadjusted part of the model that lies in one or more other images of the sequence is adjusted, whilst fixing in place a previously adjusted part of the model that lies in other images of the sequence.

Abstract: A system and method are provided for selecting an acquisition parameter for an imaging system. The acquisition parameter at least in part defines an imaging configuration of the imaging system during an imaging procedure with a patient. A depth-related map is accessed which is generated on the basis of sensor data from a camera system, wherein the camera system has a field of view which includes at least part of a field of view of the imaging system, wherein the sensor data is obtained before the imaging procedure with the patient and indicative of a distance that parts of the patient's exterior have towards the camera system. A machine learning algorithm is applied to the depth-related map to identify the acquisition parameter, which may be provided to the imaging system.

Abstract: There is provided a method and apparatus for adjusting a model of an anatomical structure in a sequence of images of the anatomical structure. The model is placed with respect to the anatomical structure in the sequence of images. A user input is received to adjust the model in a selected image of the sequence, and based on the user input, a part of the model that lies in the selected image and a previously unadjusted part of the model that lies in one or more other images of the sequence is adjusted, whilst fixing in place a previously adjusted part of the model that lies in other images of the sequence.

Abstract: Systems and methods are provided for generating and using statistical data which is indicative of a difference in shape of a type of anatomical structure between images acquired by a first imaging modality and images acquired by a second imaging modality. This statistical data may then be used to modify a first segmentation of the anatomical structure which is obtained from an image acquired by the first imaging modality so as to predict the shape of the anatomical structure in the second imaging modality, or in general, to generate a second segmentation of the anatomical structure as it may appear in the second imaging modality based on the statistical data and the first segmentation.

Abstract: There is provided a method and apparatus for segmenting two-dimensional images of an anatomical structure. A time sequence of two-dimensional images of the anatomical structure is acquired (202) and a segmentation model for the anatomical structure is acquired (204). The segmentation model comprises a plurality of segments. The acquired segmentation model is applied to the entire time sequence of two-dimensional images of the anatomical structure simultaneously in time and space to segment the time sequence of two-dimensional images by way of the plurality of segments (206).

Abstract: An apparatus, a method and a computer program for visualizing a conduction tract of a heart include adapting a generic heart model to match geometrical data of a patient's heart, where model data, corresponding to the generic heart model and indicating a shape and/or position of the conduction tract, is modified in accordance to the adaptation of the generic heart model. The modification of the model data is further refined based on electrophysiological data of the patient to produce refined model data, and the refined model data is used for generating a visualization of a refined model heart indicating a refined shape and/or refined position of the conduction tract of the patients heart.

Abstract: A system and a method are provided for analyzing an image of an aortic valve structure to enable assessment of aortic valve calcifications. The system comprises an image interface for obtaining an image of an aortic valve structure, the aortic valve structure comprising aortic valve leaflets and an aortic bulbus. The system further comprises a segmentation subsystem for segmenting the aortic valve structure in the image to obtain a segmentation of the aortic valve structure. The system further comprises an identification subsystem for identifying a calcification on the aortic valve leaflets by analyzing the image of the aortic valve structure.

Abstract: An information retrieval system (IPS). The system comprises an input interface (IN) for receiving a query related to an object of interest. A concept mapper (CM) is configured to map the query to one or more associated concept entries of a hierarchic graph data structure (ONTO). The entries in said structure encode linguistic descriptors of components of a model (GM) for said object (OB). A metric-mapper (MM) is configured to map the query to one or more metric relationship descriptors. A geo-mapper (GEO) is configured to map said concept entries against the geometric model linked to the hierarchic graph data structure to obtain spatio-numerical data associated with said linguistic descriptors. A metric component (MTC) is configured to compute one or more metric or spatial relationships between said object components based on the spatio-numerical data and the one or more metric relationship descriptors.

Abstract: A system and method are provided for use in evaluating a clinical guideline which is represented in a machine readable version by a decision tree comprising at least one node and a decision rule associated with the node. The decision rule comprises at least one variable representing a biomedical quantity. The biomedical quantity is extracted from the patient data using an ontology which defines concepts and their relationships in a medical domain of the clinical guideline and which thereby relates the variable of the decision rule to the patient data. If said extraction is not possible, a view of the patient data is presented to the user to enable the user to determine the biomedical quantity from the view. Advantageously, the user is assisted in evaluating the clinical guideline even when it is not possible to automatically extract the biomedical quantity from the patient data.

Abstract: A method is provided for generating a deformable model (300) for segmenting an anatomical structure in a medical image. The anatomical structure comprises a wall. The deformable model (300) is generated such that it comprises, in addition to two surface meshes (320, 360), an intermediate layer mesh (340) for being applied in-between a first surface layer of the wall and a second surface layer of the wall. In generating the intermediate layer mesh (340), the mesh topology of at least part (400) of the intermediate layer mesh is matched to the mesh topology of one of the surface meshes (320, 360), thereby establishing matching mesh topologies. The deformable model (300), as generated, better matches the composition of such walls, thereby providing a more accurate segmentation.

Abstract: The present invention relates to an apparatus for providing a patient specific 3D model of a body part. It is described to provide (210) at least one 2D X-ray image comprising 2D X-ray image data of a vascular structure of a patient's body part. A 3D model of the body part is provided (220), the 3D model comprising a 3D modelled vascular structure, wherein at least one parameter commands an appearance of the 3D modelled vascular structure. The 3D modelled vascular structure is confronted (230) with the 2D X-ray image data of the vascular structure to determine the at least one parameter. The 3D model is updated (240) as a function of the determined at least one parameter. A medical report is generated (250) based on information determined from the 3D model.

Abstract: The present invention relates to an apparatus for providing a synthetic representation of a vascular structure. It is described to provide (210) at least one 2D X-ray image comprising 2D X-ray image data of a vascular structure of a patient's body part is provided. A 3D model of the body part is provided (220), the 3D model comprising a 3D modelled vascular structure. A 2D projection of the 3D model of the body part is determined (230), the 2D projection of the 3D model of the body part comprising a 2D projection of the 3D modelled vascular structure. The 3D model of the body part is transformed (240). The transform of the 3D model of the body part comprises a determination of the pose of the 3D model of the body part such that a 2D projection of the 3D modelled vascular structure associated with the transformed 3D model of the body part is representative of the 2D X-ray image data of the vascular structure of the patient's body part.

Abstract: Interventional medical procedures involve a complex sequence of actions, often involving many different medical professionals and items of equipment. These actions, and their notable attributes, should be recorded in detail, in case they are required during a consultation in the future. A typical medical interventional procedure could require hundreds, or even thousands, of actions to be recorded. This places demands on a medical practitioner during the intervention. Typically, important information is dictated into a report after an intervention. Attempting to produce the report by traditional means, such as by dictation, after the intervention is time-consuming. The proposed approach enables the formation of clinical reports based on structured interventional medical reporting data recorded during a medical intervention in an easier, and more accurate way. Interventional procedure status indications are used which may be derived from existing medical equipment, or information inputs.

Abstract: The invention relates to a system (100) for computing a risk, the risk relating to injuring an anatomical structure by a medical device during a medical procedure, the system comprising: a structure unit (110) for obtaining a position of the anatomical structure; a device unit (120) for obtaining a position of the medical device; and a risk unit (130) for computing the risk relating to injuring the anatomical structure, based on the position of the medical device and the position of the anatomical structure. The system (100) may be used for planning a path of a medical device, which path minimizes said risk, or for monitoring said risk during the medical procedure.

Abstract: A system (100) is provided for performing a model-based segmentation of an anatomical structure in a medical image. The system comprises a processor (140) configured for performing a model-based segmentation of the anatomical structure by applying a deformable model to image data (042). Moreover, definition data (220) is provided which defines a geometric relation between a first part and a second part of the deformable model of which a corresponding first part of the anatomical structure is presumed to be better visible in the image data than a corresponding second part of the anatomical structure. The definition data is then used to adjust a fit of the second part of the deformable model. As a result, a better fit of the second part of the deformable model to the second part of the anatomical structure is obtained despite said part being relatively poorly visible in the image data.

Abstract: The present application describes a system (100) and method for detecting and labeling structures of interest. The system includes a current patient study database (102) containing a current patient study (200) with clinical contextual information (706). The system also includes an image metadata processing engine (118) configured to extract metadata for preparing an input for an anatomical structure classifier (608), a natural language processing engine (120) configured to extract clinical context information (706) from the prior patient documents, an anatomical structure detection and labeling engine (718), and a display device (108) configured to display findings from the current patient study. The anatomical structure detection and labeling engine (718) is configured to identify and label one or more structures of interest (716) from the extracted metadata and clinical context information (706). The processor (112) is also configured to aggregate series level data.

Abstract: A system and a method are provided for analyzing an image of an aortic valve structure to enable assessment of aortic valve calcifications. The system comprises an image interface for obtaining an image of an aortic valve structure, the aortic valve structure comprising aortic valve leaflets and an aortic bulbus. The system further comprises a segmentation subsystem for segmenting the aortic valve structure in the image to obtain a segmentation of the aortic valve structure. The system further comprises an identification subsystem for identifying a calcification on the aortic valve leaflets by analyzing the image of the aortic valve structure.

Abstract: A system (20) for interacting with a three-dimensional object dataset comprises a signal input (21) for receiving a signal from an interaction device (34) comprising a touch sensitive surface (35) having a typical shape of at least part of an object represented by the three-dimensional object dataset, wherein the signal is indicative of a location on the touch sensitive surface (35) that is touched. The system further comprises a mapping unit (22) for mapping the touched location to a corresponding point of the object represented by the three-dimensional object dataset. The three-dimensional object dataset is based on a signal obtained from a scanner (24) arranged for scanning the object.

Abstract: A system (100) is provided for performing a model-based segmentation of an anatomical structure in a medical image. The system comprises a processor (140) configured for performing a model-based segmentation of the anatomical structure by applying a deformable model to image data (042). Moreover, definition data (220) is provided which defines a geometric relation between a first part and a second part of the deformable model of which a corresponding first part of the anatomical structure is presumed to be better visible in the image data than a corresponding second part of the anatomical structure. The definition data is then used to adjust a fit of the second part of the deformable model. As a result, a better fit of the second part of the deformable model to the second part of the anatomical structure is obtained despite said part being relatively poorly visible in the image data.