Abstract: The present disclosure relates to a system for patient-specific intervention planning, the system comprising a physical model of an anatomical structure, wherein the physical model is a patient-specific model based on medical image data; a virtual model of the anatomical structure, wherein the virtual model is a patient-specific model based on medical image data; a tracking device configured to track a position of a physical representation of an interventional tool with respect to the physical model of the anatomical structure; a processor configured to perform the step of: registering the physical model of the anatomical structure with the virtual model of the anatomical structure and registering the physical representation of the interventional tool with a virtual representation of the interventional tool based on the position of the physical representation of the interventional tool and the physical model of the anatomical structure.

Abstract: The present disclosure relates to a system for patient-specific intervention planning, the system comprising a physical model of an anatomical structure, wherein the physical model is a patient-specific model based on medical image data; a virtual model of the anatomical structure, wherein the virtual model is a patient-specific model based on medical image data; a tracking device configured to track a position of a physical representation of an interventional tool with respect to the physical model of the anatomical structure; a processor configured to perform the step of: registering the physical model of the anatomical structure with the virtual model of the anatomical structure and registering the physical representation of the interventional tool with a virtual representation of the interventional tool based on the position of the physical representation of the interventional tool and the physical model of the anatomical structure.

Abstract: Disclosed is a method (100) of visualizing a sequence of 3D ultrasound images of an object (10) in motion, wherein said motion is a complex motion composed of motion components from a plurality of origins, the method comprising acquiring (120) said sequence of 3D ultrasound images; providing (130) a motion tracking model modelling a contribution to the complex motion, said contribution originating from a subset of said motion components; determining (150) said complex motion from the first and second 3D ultrasound images; and visualizing (160) a contribution of the motion tracking model to the complex motion of said object in order to obtain a motion-decomposed visualization of said complex motion. A computer program product for implementing such a method on an ultrasound system and an ultrasound system including such a computer program product are also disclosed.

Abstract: Disclosed is a method (100) of visualizing a sequence of 3D ultrasound images of an object (10) in motion, wherein said motion is a complex motion composed of motion components from a plurality of origins, the method comprising acquiring (120) said sequence of 3D ultra-sound images; providing (130) a motion tracking model modelling a contribution to the complex motion, said contribution originating from a subset of said motion components; determining (150) said complex motion from the first and second 3D ultrasound images; and visualizing (160) a contribution of the motion tracking model to the complex motion of said object in order to obtain a motion-decomposed visualization of said complex motion. A computer program product for implementing such a method on an ultrasound system and an ultrasound system including such a computer program product are also disclosed.

Abstract: The present invention relates to visualizing information of an object.

Abstract: A device for localization of an object of interest in a subject includes a registration unit for registering a 3D-representation of the subject having a plurality of segments corresponding to a plurality of structural regions of the subject, with a 2D-image. The registration unit is configured to define a plurality of areas in the image such that at least one area of the plurality of areas is associated with a respective region of the plurality of regions. A localization unit is configured to localize the object, and extract an indication of the object from the image by processing the image. The processing is limited to an object area of the plurality of areas which is associated with a predetermined object region.

Abstract: The present invention relates to visualizing information of an object.

Abstract: The present invention relates to a device, a method and a computer program which allow for the localization of an object of interest in a subject. The device includes a registration unit (25) for registering (120) a 3D-representation of the subject, which comprises a plurality of segments corresponding to a plurality of structural regions of the subject, with a 2D-image (200), wherein the registration unit is adapted for defining a plurality of areas (205, 210, 215) in the image such that at least one area of the plurality of areas is associated with a respective region of the plurality of regions, and a localization unit (30) for localizing (125) the object, extracting an indication of the object from the image by processing the image, wherein the processing is limited to an object area of the plurality of areas which is associated with a predetermined object region.

Abstract: A method for determining the presence or absence of malignant features in medical images, wherein a plurality of base comparison or training images of various types of lesions taken of actual patient is examined by one or more image reading experts to create a first database array. Low-level features of each of the lesions in the same plurality of base comparisons or training images arc determined using one or more image processing algorithms to obtain a second database array set. The first and second database array set are combined to create a training database array set which is input to a learning system that discovers/learns a classifier that maps from a subset of the low-level features to the expert's evaluation in the first database array set. The classifier is used to determine the presence of a particular mid-level feature in an image of lesion in a patient based solely on the image.