Abstract: The disclosure relates to a method of determining a transformation between coordinate frames of sets of image data. The method includes receiving a model of a structure extracted from first source image data, the first source image data being generated according to a first imaging modality and having a first data format, wherein the model has a second data format, different from the first data format. The method also includes determining, using an intelligent agent, a transformation between coordinate frames of the model and first target image data, the first target image data being generated according to a second imaging modality different to the first imaging modality.

Abstract: A method of training a computer system for use in determining a transformation between coordinate frames of image data representing an imaged subject. The method trains a learning agent according to a machine learning algorithm, to determine a transformation between respective coordinate frames of a number of different views of an anatomical structure simulated using a 3D model. The views are images containing labels. The learning agent includes a domain classifier comprising a feature map generated by the learning agent during the training operation. The classifier is configured to generate a classification output indicating whether image data is synthesized or real images data. Training includes using unlabeled real image data to training the computer system to determine a transformation between a coordinate frame of a synthesized view of the imaged structure and a view of the structure within a real image.

Abstract: A method of extracting mechanical activation of the left ventricle from a sequence of contrasted X-ray fluoroscopy images is provided. The method includes: processing the image sequence to perform segmentation of the coronary veins; annotating branches of the segmented coronary veins; tracking the positions of the annotations throughout the fluoroscopy image sequence; computing the principle components of the motion of the annotations from the tracked positions; projecting the motion of the annotations to the axis corresponding to a first principle component; and analyzing the resulting motion curves to identify a latest activating region of the left ventricle.

Abstract: A method of training a computer system for use in determining a transformation between coordinate frames of image data representing an imaged subject. The method trains a learning agent according to a machine learning algorithm, to determine a transformation between respective coordinate frames of a number of different views of an anatomical structure simulated using a 3D model. The views are images containing labels. The learning agent includes a domain classifier comprising a feature map generated by the learning agent during the training operation. The classifier is configured to generate a classification output indicating whether image data is synthesized or real images data. Training includes using unlabeled real image data to training the computer system to determine a transformation between a coordinate frame of a synthesized view of the imaged structure and a view of the structure within a real image.

Abstract: In a method and processor for evaluating a contrast agent-enhanced two-dimensional magnetic resonance slice image of a heart of a patient in order to determine picture elements revealing contrast agent deposits in the myocardium, an endocardium contour in the magnetic resonance slice image, taking into consideration deposition information describing picture elements potentially revealing contrast agent deposits and determined by image analysis on the basis of a shape assumption for the heart structure that is to be examined, in particular the left ventricle, such that picture elements potentially revealing contrast agent deposits are avoided as much as possible as a contour component. An epicardium contour enclosing the endocardium contour is then determined. Picture elements are marked that indicate contrast agent enhancement in the myocardium lying between the epicardium contour and the endocardium contour as contrast agent deposit.

Abstract: A method of extracting mechanical activation of the left ventricle from a sequence of contrasted X-ray fluoroscopy images is provided. The method includes: processing the image sequence to perform segmentation of the coronary veins; annotating branches of the segmented coronary veins; tracking the positions of the annotations throughout the fluoroscopy image sequence; computing the principle components of the motion of the annotations from the tracked positions; projecting the motion of the annotations to the axis corresponding to a first principle component; and analyzing the resulting motion curves to identify a latest activating region of the left ventricle.

Abstract: The disclosure relates to a method of determining a transformation between coordinate frames of sets of image data. The method includes receiving a model of a structure extracted from first source image data, the first source image data being generated according to a first imaging modality and having a first data format, wherein the model has a second data format, different from the first data format. The method also includes determining, using an intelligent agent, a transformation between coordinate frames of the model and first target image data, the first target image data being generated according to a second imaging modality different to the first imaging modality.

Abstract: In a method and processor for evaluating a contrast agent-enhanced two-dimensional magnetic resonance slice image of a heart of a patient in order to determine picture elements revealing contrast agent deposits in the myocardium, an endocardium contour in the magnetic resonance slice image, taking into consideration deposition information describing picture elements potentially revealing contrast agent deposits and determined by image analysis on the basis of a shape assumption for the heart structure that is to be examined, in particular the left ventricle, such that picture elements potentially revealing contrast agent deposits are avoided as much as possible as a contour component. An epicardium contour enclosing the endocardium contour is then determined. Picture elements are marked that indicate contrast agent enhancement in the myocardium lying between the epicardium contour and the endocardium contour as contrast agent deposit.

Abstract: In a method and magnetic resonance apparatus for segmenting a balloon-type volume having an inner surface and an outer surface in an image data record, that is provided to a computer, the image data record at least partially mapping a balloon-type volume, the computer is provided with a starting area and determines a first boundary surface as an inner surface of the balloon-type volume. The computer is provided with a starting surface in the balloon-type volume, and determines a second boundary surface as an outer surface of the balloon-type volume on the basis of the starting surface. The balloon-type volume is determined in the computer as a volume within the first boundary surface and the second boundary surface.