Abstract: The invention describes a method for the geometrical analysis of scan data from oral structures, comprising the steps of selecting a number of parameterized tooth models of desired tooth types according to the scan data to be analyzed, whereby each tooth model comprises at least one boundary line whose path is defined by line parameters and which divides a tooth model in at least one active adjustment area and at least one inactive adjustment area, and segmenting the scan data on the basis of individualized tooth models and individualized boundary lines and/or determining at least one boundary line in the scan data. The invention further describes a method of generating a model database; and an analysis system for the geometrical analysis of scan data from oral structures.

Abstract: The invention describes a method for the geometrical analysis of scan data (D) from oral structures, comprising the steps of selecting a number of parameterized tooth models (M) of desired tooth types according to the scan data (D) to be analyzed, whereby the parameterization is performed on the basis of model parameters comprising position parameters and/or shape parameters and line parameters, and whereby each tooth model (M) comprises at least one boundary line (LS, LP) whose path is defined by line parameters and which divides a tooth model (M) in at least one active adjustment area (AA) and at least one inactive adjustment area (AI), adjusting the tooth models (M) and their boundary lines (LS, LP) to the scan data (D) for individualization, whereby the individualization is performed by variation of model parameters, and whereby the active adjustment areas (AA) of the tooth models (M) are weighted more than the inactive adjustment areas (AI), segmenting the scan data (D) on the basis of the individualized

Abstract: The invention describes a method of determining virtual tooth restorations on the basis of scan data (D) of oral structures, wherein a model database (DB) comprising a number of parameterized tooth models for each of several tooth types is used, whereby the parameterization is carried out on the basis of model parameters comprising position parameters and/or shape parameters and whereby each tooth model (M) is linked with a number of tooth models (M) of the same tooth type, and wherein, for each desired tooth type, an optimal tooth model (M) in the model database (DB) is determined by means of an iterative method in which initially at least one start tooth model (M) of the desired tooth type is selected from the model database (DB), and subsequently, commencing with this start tooth model (M), in each iteration step (S) a tooth model (M) is tested with regard to a quality value, wherein for individualization, the tooth model (M) currently in test is adjusted to the scan data (D) by varying model parameters an

Abstract: A method is for segmentation of section image data of an examination object, in which a target structure is determined in the section image data and an anatomical norm model is selected whose geometry can be varied on the basis of model parameters. The model parameters are organized hierarchically on the basis of their influence on the anatomical overall geometry of the model. The norm model is matched to the target structure for individualization purposes in a number of iteration steps, with the number of model parameters which can be set being increased in accordance with the hierarchical organization as the number of iteration steps increases. Finally, all of those pixels within the section image data are selected which lie within a contour of the individualized model or of model part, or which differ from this by at most a specific difference value. A corresponding image processing system is also described.

Abstract: In a method for determination of patient-related information regarding the position and orientation of slice image exposures in magnetic resonance tomographic examinations, initial MR overview exposures (magnetic resonance overview exposures) of the body of the patient are produced. Using these initial MR overview exposures, a predetermined, parameterized anatomical body model (i.e. an anatomical body model) with specific variable model parameters is then individualized (customized). The determination of the patient-related information about the position and orientation of the subsequent (diagnostic) slice image exposures then ensues on the basis of the relative position of the slice image exposures with regard to the individualized body model. In the individualization, by variation of the model parameters the body model is adapted to specific structures determined from the initial MR overview exposures, which specific structures advantageously represent the body surface of the patient.

Abstract: In a method and control device for the operation of a magnetic resonance tomography apparatus, initially an anatomical normal model whose geometry is variable is selected for an examination subject to be examined dependent on a diagnostic inquiry. Then a number of overview images of a region of the examination subject are obtained, with various overview scan parameters with which the acquisition of the overview images is controlled being established dependent on the selected anatomical normal model. In the slice image data of the acquired overview images, a target structure is determined and the normal model is individualized for adaptation to the determined target structure. Scan parameters for control of the magnetic resonance tomography apparatus for acquisition of subsequent slice images dependent on the selected normal model and a diagnostic inquiry are then selected and individualized corresponding to the individualized normal model.

Abstract: A method is for automatically producing result images for an examination object using section image data. In this case, a target structure is first of all ascertained in the section image data on the basis of a diagnostic questionnaire, and the target structure is taken as a basis for selecting an anatomical norm model whose geometry can be varied using model parameters. The norm model is automatically adapted to the target structure. The section image data are then segmented on the basis of the adapted norm model, with anatomical structures of the examination object which are relevant to the diagnostic questionnaire being separated by selecting all of the pixels within the section image data which are situated within a contour of the adapted norm model and/or at least one model part in line with the relevant structures or have a maximum discrepancy therefrom by a particular value. The relevant structures are then visually displayed separately and/or are stored for later visual display.

Abstract: A method is for segmentation of section image data of an examination object, in which a target structure is determined in the section image data and an anatomical norm model is selected whose geometry can be varied on the basis of model parameters. The model parameters are organized hierarchically on the basis of their influence on the anatomical overall geometry of the model. The norm model is matched to the target structure for individualization purposes in a number of iteration steps, with the number of model parameters which can be set being increased in accordance with the hierarchical organization as the number of iteration steps increases. Finally, all of those pixels within the section image data are selected which lie within a contour of the individualized model or of model part, or which differ from this by at most a specific difference value. A corresponding image processing system is also described.