Koninklijke Philips Corporation N.v.

University of the Basque Country

Basque Center for Macromolecular Design and Engine

Basque Center for Macromolecular Design and Engineering, Polymat Fundazioa

Philips Intellectual Property & Standards Gmbh

Fabian Wenzel

Thomas Heiko Stehle

Carsten Meyer

Stewart Young

Martin Bergtholdt

Lyubomir Georgiev Zagorchev

Frank Olaf Thiele

Jochen Peters

Thomas Netsch

Astrid Ruth Franz

Sebastian Peter Michael Dries

Tom Brosch

Johan Michiel Den Harder

Roel Truyen

Jean-Pierre Franciscus Alexander Maria Ermes

Ralph Buchert

Rafael Wiemker

Jochen Kruecker

Peter Boernert

Jens Von Berg

Michael Harald Kuhn

Thomas Erik Amthor

Heinrich Schulz

Christopher Stephen Hall

Axel Saalbach

Kirsten Regina Meetz

Mariya Ivanova Doneva

Arne Ewald

Tim Philipp Harder

Ingwer Curt Carlsen

Nick Flaeschner

Elizabeth Anne Moore

Shiv Sabesan

Eliza Teodora Orasanu

Katerina Georgopoulou

Jose Ramon Leiza

José Ramón Leiza

Miren Aguirre Arrese

Torjoern Vik

Michael Kuhn

Ingwer C Carlsen

The present invention refers to a method for producing polymeric compositions, preferably in the form of water-based (i.e. waterborne) compositions, more preferably dispersions (i.e. emulsions or latices), which are particularly useful as or in adhesives, especially pressure-sensitive adhesives, particularly pressure-sensitive adhesives degradable under basic conditions, as well as to the polymeric compositions thus produced and to their applications.

Method for producing a polymeric composition and polymeric composition thus produced as well as applications thereof, especially as or in pressure sensitive adhesives

The invention relates to a regions identifying apparatus () for identifying regions in an image like a computed tomography image showing a brain. A model providing unit () provides a three-dimensional model of a head of a living being, wherein the three-dimensional model includes Alberta Stroke Program Early CT Score (ASPECTS) regions of a brain, and a regions identifying unit () identifies ASPECTS regions in the three-dimensional image by applying the three-dimensional model to the three-dimensional image. This allows for an accurate, automatic identification of the ASPECTS regions independently of the orientation of the head in an imaging system, independently of an image slice thickness and also independently of a respective user like a physician. This leads to imaging an improved accuracy of determining the ASPECTS regions which allows for an improved quantification of ischemic changes in the brain after stroke. This in turn also allows for an improved treatment recommendation.

Apparatus for identifying regions in a brain image

A method () that encodes electrode locations to a mean scalp mesh for adaptation to subsequent image scans.

Automatic EEG sensor registration

The present disclosure relates to a method for medical imaging method for locating anatomical landmarks of a predetermining defined anatomy. The method comprises: a) providing a machine learning model for predicting anatomical landmarks in image data obtained using a set of acquisition parameters and for predicting a subsequent set of acquisition parameters of the set of acquisition parameters for subsequent acquisition of image data; b) determining 5 a current set of acquisition parameters; c) receiving survey image data representing a slice of the anatomy, the survey image data having the current set of current acquisition parameters; d) identifying anatomical landmarks in the received image data using the machine learning model; e) predicting another set of acquisition parameters using the machine learning model and repeating steps c)-e) for a predefined number of repetitions using the predicted set of 10 acquisition parameters as the current set of parameters; and f) providing the identified anatomical landmarks.

Artificial intelligence-enabled localization of anatomical landmarks

There is provided a computer-implemented method and system () for determining regions of hyperdense lung parenchyma in an image of a lung. The system () comprises a memory () comprising instruction data representing a set of instructions and a processor () configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor (), cause the processor () to locate a vessel in the image, determine a density of lung parenchyma in a region of the image that neighbours the located vessel, and determine whether the region of the image comprises hyperdense lung parenchyma based on the determined density, hyperdense lung parenchyma having a density greater than &#x2212;800 HU.

Determining regions of hyperdense lung tissue in an image of a lung

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 invention provides for a magnetic resonance imaging system () for acquiring MRF magnetic resonance data () from a subject () within a region of interest (). The magnetic resonance imaging system comprises a processor () for controlling the magnetic resonance imaging system and a memory () for storing machine executable instructions () and MRF pulse sequence commands (). The MRF pulse sequence commands are configured for controlling the magnetic resonance imaging system to acquire the MRF magnetic resonance data according to a magnetic resonance fingerprinting protocol. Execution of the machine executable instructions causes the processor to: acquire () the MRF magnetic resonance data for the region of interest by controlling the magnetic resonance imaging system with the MRF pulse sequence commands; receive () at least one magnetic resonance image () descriptive of the region of interest; identify () anatomical regions () within the region of interest using an anatomical model (); select () a local magnetic resonance fingerprinting dictionary () from a set of magnetic resonance fingerprinting dictionaries for each of the anatomical regions, wherein the local magnetic resonance fingerprinting dictionary comprises a listing of calculated MRF signals for a set of predetermined substances specific to each of the anatomical regions; and calculate () a composition mapping () of the predetermined substances for each of the anatomical regions using the MRF magnetic resonance data and the local magnetic resonance fingerprinting dictionary, wherein the composition mapping is a spatial average within each of the anatomical regions.

Selection of magnetic resonance fingerprinting dictionaries for anatomical regions

The invention provides for a medical instrument () comprising a processor () and a memory () containing machine executable instructions (). Execution of the machine executable instructions causes the processor to: receive () a first magnetic resonance image data set () descriptive of a first region of interest () of a subject () and receive () at least one second magnetic resonance image data set (') descriptive of a second region of interest () of the subject. The first region of interest at least partially comprises the second region of interest. Execution of the machine executable instructions further cause the processor to receive () an analysis region () within both the first region of interest and within the second region of interest. Execution of the machine executable instructions further cause the processor to construct () a cost function comprising an intra-scan homogeneity measure separately for the first magnetic resonance image data set and separately for each of the at least one second magnetic resonance image data set. The cost function further comprises an inter-scan similarity measure calculated using both the first magnetic resonance image data set and each of the at least one second magnetic resonance image data set. Execution of the machine executable instructions further cause the processor to by performing an optimization () of the cost function by calculating a first intensity correction map () for the first magnetic resonance image data set using an intensity correction algorithm within the analysis region and at least one second intensity correction map () for each of the at least one second magnetic resonance image data set within the analysis region. Execution of the machine executable instructions further cause the processor to calculate () a first corrected magnetic resonance image () descriptive of the analysis region using the first magnetic resonance image data set and the first intensity correction map. Execution of the machine executable instructions further cause the processor to calculate () at least one second corrected magnetic resonance image () descriptive of the analysis region using the at least at least one second magnetic resonance image data set and the at least one second intensity correction map.

Intensity corrected magnetic resonance images

An image processing systemfor enabling a user to navigate through image data having at least three spatial dimensions by displaying viewsof the image data, the image processing system comprising an image devicecomprising a displayfor displaying the views of the image data and an orientation sensorfor measuring an orientation of the image device with respect to a reference orientation for providing rotation dataindicative of a device rotation of the image device, meansfor establishing a center of rotation in the image data, and an image processorfor establishing the views of the image data in relation to the device rotation by, for establishing a current view, (i) receiving the rotation data from the orientation sensor, (ii) establishing a view rotation in relation to the device rotation, and (iii) establishing the current view in dependence on the view rotation around the center of rotation with respect to a reference view.

Measurements and calibration utilizing colorimetric sensors

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 medical system () and method detects amyloid brain plaque. A positron emission tomography (PET) image of a brain is received. The PET image is generated from a radiotracer binding to amyloid brain plaque. A cortical profile is generated from the PET image. The cortical profile describes cortical tracer uptake to varying projection depths inside the cortex of the brain. The PET image is quantitatively assessed using the cortical profile and/or at least a portion of the cortical profile is displayed.

Amyloid PET brain scan quantification based on cortical profiles

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

Image processing systemfor enabling a user to navigate through image data having at least three spatial dimensions by displaying viewsof the image data, the image processing system comprising an image devicecomprising a displayfor displaying the views of the image data and an orientation sensorfor measuring an orientation of the image device with respect to a reference orientation for providing rotation dataindicative of a device rotation of the image device, meansfor establishing a center of rotation in the image data, and an image processorfor establishing the views of the image data in relation to the device rotation by, for establishing a current view, (i) receiving the rotation data from the orientation sensor, (ii) establishing a view rotation in relation to the device rotation, and (iii) establishing the current view in dependence on the view rotation around the center of rotation with respect to a reference view.

Image processing system and method using device rotation

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

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Hamburg, Germany

Fabian Wenzel