Koninklijke Philips Corporation N.v.

Philips Gmbh

Thomas Heiko Stehle

Fabian Wenzel

Carsten Meyer

Jochen Peters

Juergen Weese

Frank Michael Weber

Lyubomir Georgiev Zagorchev

Martin Bergtholdt

Astrid Ruth Franz

Irina Wachter-Stehle

Michael Grass

Jochen Kruecker

Irina Waechter-Stehle

Heinrich Schulz

Christian Buerger

Ulrich Wolfgang Katscher

Nicole Schadewaldt

Jörg Sabczynski

Frank Bergner

Sabine Mollus

Christian Stehning

Elizabeth Anne Moore

Irina Wächter-Stehle

Alex Saalbach

The present invention relates to an apparatus () for correcting computer tomography ('CT') X-ray data acquired at high relative pitch, the apparatus comprising: an input unit (); a processing unit (); and an output unit (). The input unit is configured to provide the processing unit with CT X-ray data of a body part of a person acquired at high relative pitch. The processing unit is configured to determine CT slice reconstruction data of the body part of the person with no or reduced high relative pitch operation reconstruction artefacts using a machine learning algorithm. The machine learning algorithm was trained on the basis of CT slice reconstruction data, and wherein the CT slice reconstruction data comprised first CT slice reconstruction data with high relative pitch reconstruction artefacts and comprised second CT slice reconstruction data with less, less severe, or no high relative pitch reconstruction artefacts. The output unit is configured to output the CT slice reconstruction data of the body part of the person.

Apparatus for computer tomography X-ray data acquired at high relative pitch

The invention relates to an ultrasound system for imaging a volumetric region comprising a region of interest (ROI). The system comprises a probe; an ultrasound wave controlling unit adapted to control ultrasound wave transmission and provide ultrasound image data of the volumetric region; an image processor; and a ROI identifier, which is adapted to generate identification data indicating the ROI within the volumetric region; wherein the ultrasound wave transmission is configurable by a plurality of use cases in response to respective identifiers of said use cases, each use case being associated with a particular imaging procedure and comprising an anatomical model for said imaging procedure; and wherein the ROI identifier is configurable by the respective anatomical models of said use cases. A method of configuring such an ultrasound system is also disclosed.

Intelligent ultrasound system

An ultrasound system is disclosed comprising an ultrasound transducer array () comprising a plurality of ultrasound transducer cells (), each of said cell having an independently adjustable position and/or orientation such as to conform an ultrasound transmitting surface of the cell to a region of a body and a controller (). The controller is configured to register the respective ultrasound transducer cells by simultaneously operating at least two ultrasound transducer cells in a transmit mode in which the cells transmit distinguishable ultrasound signals and operating the remaining ultrasound transducer cells in a receive mode. The controller extracts time-of-flight information of the respective ultrasound signals between transmitter and receiver and by systematically selecting different ultrasound transducer cells as transmitters, the controller collects sufficient time-of-flight information from which the respective position and/or relative orientation of the ultrasound transducer cells within the ultrasound transducer array may be derived. A method for operating the ultrasound system in this manner as well as a computer program product is also disclosed.

Ultrasound system, method and computer program product

A controller for preparing an image for segmenting includes a memory that stores instructions, and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to perform a process that includes displaying a first modeled tissue structure of a first type, and displaying an image of a first tissue structure of the first type separate from the first modeled tissue structure. The process also includes identifying, on the first modeled tissue structure, landmarks on the first modeled tissue structure for identification on the image of the first tissue structure, and sequentially accentuating each landmark on the first modeled tissue structure. The processor identifies locations on the image of the first tissue structure for each landmark on the first modeled tissue structure. The landmarks on the first modeled tissue structure are mapped to the locations identified on the image of the first tissue structure.

Landmark visualization for medical image segmentation

A brachytherapy treatment planning system includes a processor that: receives a planning image corresponding to at least a portion of a prostate; generates a brachytherapy treatment plan comprising, for each of a plurality of brachytherapy seeds or catheters, a corresponding brachytherapy seed or catheter position in the planning image such that the plurality of brachytherapy seed or catheter positions in the planning image together satisfy a desired radioactive dose objective in the prostate; receives a pre-treatment image corresponding to the at least a portion of a prostate; and maps each brachytherapy seed or catheter position in the planning image to a corresponding position in the pre-treatment image by performing a registration between the planning image and the pre-treatment image.

Brachytherapy treatment planning system

The present invention relates to a medical imaging system () for planning an implantation of a cardiac implant (), comprising:

Medical imaging system

The present invention relates to medical image editing. In order to facilitate the medical image editing process, a medical image editing device () is provided that comprises a processor unit (), an output unit (), and an interface unit (). The processor unit () is configured to provide a 3D surface model of an anatomical structure of an object of interest. The 3D surface model comprises a plurality of surface sub-portions. The surface sub-portions each comprise a number of vertices, and each vertex is assigned by a ranking value. The processor unit () is further configured to identify at least one vertex of vertices adjacent to the determined point of interest as an intended vertex. The identification is based on a function of a detected proximity distance to the point of interest and the assigned ranking value. The output unit () is configured to provide a visual presentation of the 3D surface model. The interface unit () is configured to determine a point of interest in the visual presentation of the 3D surface model by interaction of a user. The interface unitis further configured to modify the 3D surface model by displacing the intended vertex by manual user interaction. In an example, the output unit () is a display configured to display the 3D surface model directly to the user ().

Medical image editing

A symmetric model representing anatomical structures of the brain is adapted to a brain scan image with a transform. First and second points provided on first and second hemispheres of the brain image and a patient-specific symmetric anatomical model of the brain is computed based on the transformation.

Improving symmetry in brain scans

A system and method are provided for brain tissue classification, which involves applying an automated tissue classification technique to an image of a brain based on a prior probability map, thereby obtaining a tissue classification map of the brain. A user is enabled to, using a user interaction subsystem, provide user feedback which is indicative of a) an area of misclassification in the tissue classification map and b) a correction of the misclassification. The prior probability map is then adjusted based on the user feedback to obtain an adjusted prior probability map, and the automated tissue classification technique is re-applied to the image based on the adjusted prior probability map. An advantage over a direct correction of the tissue classification map may be that the user does not need to indicate the area of misclassification or the correction of the misclassification with a highest degree of accuracy. Rather, it may suffice to provide an approximate indication thereof.

Brain tissue classification

A system and method are provided for interactive editing of a mesh which has been applied to a three-dimensional (3D) image to segment an anatomical structure shown therein. To facilitate the interactive editing of the applied mesh, a view of the 3D image is generated which shows a mesh part to be edited, with the view being established based on a local orientation of the mesh part. Advantageously, the view may be generated to be substantially orthogonally to the mesh part, or to a centerline of the anatomical structure which is determined as a function of the mesh part. Accordingly, an orthogonal view is established which facilitates the user in carrying out the editing action with respect to the mesh part. It is therefore not needed for the user to manually navigate through the 3D image to obtain a view which is suitable for mesh editing, which is typically time consuming.

Interactive mesh editing

An electric properties tomography method for reconstructing a spatial distribution of electric conductivity (&#x3c3;) from magnetic resonance image data representative of a magnetic resonance image of at least a portion of a subject of interest (), the spatial distribution covering at least a portion of the area of the magnetic resonance image, and the method comprising following steps:&#x2014;segmenting the magnetic resonance image,&#x2014;extrapolating acquired phase values, &#x2014;replacing acquired phase values by the extrapolated phase values,&#x2014;transforming into the frequency domain,&#x2014;multiplying a frequency domain-transformed numerical second derivative by the acquired phase values and the frequency domain-transformed numerical second derivative by the extrapolated phase values, respectively, and&#x2014;transforming the result of the multiplying into the spatial domain. Also covered are a corresponding MRI system and a software module.

EPT method of electric conductivity reconstruction with enhanced stability and speed

An apparatus and related method for image viewing. The apparatus (V) allows to store, learn and remember preferred user views &#x3b1;for each anatomical structure F-Fof interest. In any new image, the apparatus (V) affords automatically generating the preferred by the user for one or more of the structures (F-F) by a simple user input operation such as clicking with a mouse (PT) on any position within the displayed structure of interest (F-F).

Preferred view generation on structure level based on user preferences

An image processing apparatus and related method. The apparatus (PP) comprises an input port (IN), a classifier (CLS) and an output port (OUT). The input port is capable of receiving an image of an object acquired at a field of view (FoV) by an imager (USP). The image records a pose of the object corresponding to the imager's field of view (FoV). The classifier (CLA) is configured to use a geometric model of the object to determine, from a collection of pre-defined candidate poses, the pose of the object as recorded in the image. The output port (OUT) is configured to output pose parameters descriptive of the determined pose.

View classification-based model initialization

The present invention relates to a medical imaging system () for planning an implantation of a cardiac implant (), comprising: a receiving unit () for receiving a plurality of three-dimensional (3D) cardiac images (') showing different conditions of a heart () during a cardiac cycle; a segmentation unit () for segmenting within the plurality of 3D cardiac images (&#x2032;) a target implant region () and a locally adjacent region () that could interfere with the cardiac implant (); a simulation unit () for simulating the implantation of the cardiac implant () within the target implant region () in at least two of the plurality of 3D cardiac images (&#x2032;); a collision evaluation unit () for evaluating an overlap () of the simulated cardiac implant () with the segmented locally adjacent region () in at least two of the plurality of 3D cardiac images (&#x2032;); and a feedback unit () for providing feedback information to a user concerning the evaluated overlap ().

Planning an implantation of a cardiac implant

A system () and method is provided for performing a model-based segmentation of an anatomical structure in a medical image of a patient. The medical image () is accessed. Moreover, model data () is provided which defines a deformable model for segmenting the type of anatomical structure. The model-based segmentation of the anatomical structure is performed by adapting the deformable model to the anatomical structure in the medical image using an adaptation technique. In accordance with the present invention, performing the model based segmentation further comprises determining from patient data () medical information which is predictive of an appearance of the anatomical structure in the medical image, and adjusting or setting a segmentation parameter based on the medical information so as to adjust the model-based segmentation to said predicted appearance of the anatomical structure in the medical image, the segmentation parameter being a parameter of i) the deformable model or ii) the adaptation technique. Advantageously, the system and method are enabled to better cope with the inter-patient and inter-disease-stage variability in the appearance of anatomical structures.

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Hamburg, Germany

Thomas Heiko Stehle