Abstract: Systems and methods for language-guided navigation assistance for medical image acquisition are provided. An initial image depicting a view of an image acquisition device at an initial position and a target image depicting a view of a target position are received. A trajectory between the initial position and the target position is determined based on the initial image and the target image. Text-based descriptions are generated for each step of the trajectory using a machine learning based vision-language model. One or more keyframes are selected from the trajectory based on the text-based descriptions. A particular natural language instruction for navigating the image acquisition device to a particular keyframe of the one or more keyframes to are generated. The natural language instructions are output.

Abstract: For movement of medical sensors for medical imaging, an artificial intelligence (AI) is trained using a contrastive reinforcement learning (CRL) framework. Simulation may be used to provide the training data. For training, the sampling for a given input instance in CRL may use trajectories simulated from different patients for better contrast. CRL, with or without the simulation feature and/or the sampling feature, may provide more generalized navigation, such as in interventional or diagnostic settings.

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: Embodiments of the invention provide structures for a force sensor, and force sensors using such structures, which are compact and easy to manufacture, for example by 3D printing. In particular the structures comprise a pair of stacked ring sensor elements, the ring sensor elements in turn being formed by upper and lower ring elements joined together at points around the circumference thereof by resiliently mounted connection bars. The connection bars may extend in the same plane as the rings, in which case sensitivity to torque about the axis of the rings is much reduced, such that a five-axis sensor is effectively obtained, or the connection bars may extend obliquely between the upper and lower rings of each sensor element, such that they have a directional component in the direction of the axis of the rings (the rings of each element being co-axially stacked).

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 for registering image data sets of a target region of a patient includes selecting a first anatomical structure only or at least partially only visible in the first image data set, and a second anatomical structure only or at least partially only visible in the second image data set, such that there is a known geometrical relationship between extended segments of the anatomical structures; automatically determining a first geometry information describing the geometry of at least a part of the first anatomical structure and a second geometry information describing the geometry of at least a part of the second anatomical structure, neither information being sufficient to enable registration of the image data sets on its own; automatically optimizing transformation parameters describing a rigid transformation of one of the anatomical structures with respect to the other and geometrical correspondences; and determining registration information from the optimized transformation parameters.

Abstract: In a method for visualization of scar tissue in medical imaging data of a heart, medical imaging data representing a heart myocardium and scar tissue within the heart myocardium are obtained and provided to a computer. The computer deviates the thickness of the myocardium into a number of layers and calculates the presence and distribution of scar tissue within each of the layers. The scar tissue is shown in a visualization of the myocardium; and a user is provided with controls to allow the user to select which of the layers of scar tissue is visualised.

Abstract: A method for registering image data sets of a target region of a patient includes selecting a first anatomical structure only or at least partially only visible in the first image data set, and a second anatomical structure only or at least partially only visible in the second image data set, such that there is a known geometrical relationship between extended segments of the anatomical structures; automatically determining a first geometry information describing the geometry of at least a part of the first anatomical structure and a second geometry information describing the geometry of at least a part of the second anatomical structure, neither information being sufficient to enable registration of the image data sets on its own; automatically optimizing transformation parameters describing a rigid transformation of one of the anatomical structures with respect to the other and geometrical correspondences; and determining registration information from the optimized transformation parameters.

Abstract: In a method for visualization of scar tissue in medical imaging data of a heart, medical imaging data representing a heart myocardium and scar tissue within the heart myocardium are obtained and provided to a computer. The computer deviates the thickness of the myocardium into a number of layers and calculates the presence and distribution of scar tissue within each of the layers. The scar tissue is shown in a visualization of the myocardium; and a user is provided with controls to allow the user to select which of the layers of scar tissue is visualised.