Abstract: Disclosed is a computer-implemented method of determining an atlas element. The method encompasses acquiring model image data that describes at least one fixed element (an anatomical element such as an anatomical body part, for example, a rib). Patient image data is acquired that describes an improvable element (an anatomical element such as an anatomical body part, for example heart). Region data is acquired, for example by assigning a homogeneous grey value to a region of the model image. The patient image is matched to the model image, wherein no matching is performed within the region. A transformation for mapping the improvable element into the region is determined based on matching. Several patient images are then mapped into the region and superimposed. An atlas element is determined based on the superimposed images. The method may be repeated using the determined anatomical atlas element as a constraint to detect further atlas elements.

Abstract: Disclosed is a computer-implemented method of determining an atlas element. The method encompasses acquiring model image data that describes at least one fixed element (an anatomical element such as an anatomical body part, for example, a rib). Patient image data is acquired that describes an improvable element (an anatomical element such as an anatomical body part, for example heart). Region data is acquired, for example by assigning a homogeneous grey value to a region of the model image. The patient image is matched to the model image, wherein no matching is performed within the region. A transformation for mapping the improvable element into the region is determined based on matching. Several patient images are then mapped into the region and superimposed. An atlas element is determined based on the superimposed images. The method may be repeated using the determined anatomical atlas element as a constraint to detect further atlas elements.

Abstract: Disclosed is a method for determining a position of a brain sulcus in the brain of a patient, the method comprising executing, on at least one processor of at least one computer, steps of: acquiring, at the at least one processor, patient image data describing a digital medical image of at least part of the brain; acquiring, at the at least one processor, atlas data describing an image-based model of the at least part of the brain; determining, by the at least one processor and based on the patient image data and the atlas data, mapping data describing a transformation between the patient image data and the atlas data; and determining, by the at least one processor and based on the patient image data and the atlas data and the mapping data, sulcus position data describing the position of the brain sulcus in the digital medical image.

Abstract: Disclosed is a method for determining a position of a brain sulcus in the brain of a patient, the method comprising executing, on at least one processor of at least one computer, steps of: acquiring, at the at least one processor, patient image data describing a digital medical image of at least part of the brain; acquiring, at the at least one processor, atlas data describing an image-based model of the at least part of the brain; determining, by the at least one processor and based on the patient image data and the atlas data, mapping data describing a transformation between the patient image data and the atlas data; and determining, by the at least one processor and based on the patient image data and the atlas data and the mapping data, sulcus position data describing the position of the brain sulcus in the digital medical image.

Abstract: A data processing method for registering patient data containing normal patient data and specific object data to atlas data not containing this specific object data, the method comprising the following steps performed by a computer: a) acquiring the patient data which comprises anatomical information of the patient including normal patient data and the specific object data of the patient; b) segmenting the specific object data in the patient data; c) acquiring atlas data; d) acquiring meta-information about components of the atlas data; e) performing a fusion of the acquired patient data excluding the segmented specific object data and the atlas data to obtain registered atlas data; and f) simulating the growth of a simulated specific object within the registered atlas data using the registered atlas data and the meta-information about components of the atlas data being adjacent to the area of the specific object to obtain registered atlas data containing a simulated grown specific object.