Abstract: Disclosed is a computer-implemented method of determining one or more position and/or orientation parameters of an anatomical structure of a body portion. The anatomical structure has a longitudinal shape defining a longitudinal axis. The method includes generating and/or reading, by a data processing system, volumetric data of at least a portion of a subject. The method further includes generating and/or reading, by the data processing system, a deformable template which provides an estimate for a location of the longitudinal axis in the portion of the subject. The method further includes matching, by the data processing system, the deformable template to the volumetric data, thereby obtaining a matched template. The matching comprises using one or more internal energy functions and one or more external energy functions for optimizing an objective function.

Abstract: The invention relates to a medical data processing method for determining the position of a region of interest serving as a start condition for conducting diffusion image-based tracking of nerve fibers. In one example, the method encompasses comparing a set of tracked nerve fibers to a model of nerve fibers contained in atlas data.

Abstract: The invention relates to a medical data processing method for determining the position of a nerve fiber based on a diffusion image-based tracking method of tracking nerve fibers. In one example, the method encompasses comparing a set of tracked nerve fibers to a model of nerve fibers contained in atlas data.

Abstract: The invention relates to a medical data processing method for determining the position of a nerve fiber based on a diffusion image-based tracking method of tracking nerve fibers. In one example, the method encompasses comparing a set of tracked nerve fibers to a model of nerve fibers contained in atlas data.

Abstract: The invention relates to a medical data processing method for determining the position of a region of interest serving as a start condition for conducting diffusion image-based tracking of nerve fibers. In one example, the method encompasses comparing a set of tracked nerve fibers to a model of nerve fibers contained in atlas data.

Abstract: A method for finding fibers in image data of a brain, comprising the steps of: matching (S2) a functional atlas of the brain to an image data set which represents a medical image of the brain; performing functional atlas segmentation (S3) in order to segment the image data set into functional areas; using (S4, S8) the segmented image data set to determine at least one seed point for a fiber tracking algorithm; and - performing (S5) fiber tracking in order to find the fiber.

Abstract: A method for finding fibers in image data of a brain, comprising the steps of: matching (S2) a functional atlas of the brain to an image data set which represents a medical image of the brain; performing functional atlas segmentation (S3) in order to segment the image data set into functional areas; using (S4, S8) the segmented image data set to determine at least one seed point for a fiber tracking algorithm; and performing (S5) fiber tracking in order to find the fiber.