Koninklijke Philips Corporation N.V.

Koninklijke Philips Electronics N.v.

Javier Olivan Bescos

Christian Haase

Romane Isabelle Marie-Bernard Gauriau

Michael Grass

Raoul Florent

Thijs Elenbaas

Peter Maria Johannes Rongen

Arjen Van Der Horst

Vincent Maurice André Auvray

Bram Antonius Philomena Van Rens

Roland Wilhelmus Maria Bullens

Holger Schmitt

Olivier Pierre Nempont

Markus Johannes Harmen Den Hartog

Jeroen Jozef Sonnemans

Roy Franciscus Petrus Van Pelt

Gereon Vogtmeier

Eberhard Sebastian Hansis

Marcel Breeuwer

Daniel Simon Anna Ruijters

Vincent Maurice Andre Auvray

Raymond Joseph Elisabeth Habets

Guillaume Julien Joseph Pizaine

Marco Verstege

Fred Simon Berend Van Nijnatten

Ronaldus Petrus Johannes Hermans

Martijn Anne Van Lavieren

Joost Frederik Peters

William Edward Peter Van Der Sterren

Pieter Gerben Eshuis

Jeroen Gerard Scheepens

Daniël Simon Anna Ruijters

Maurice Alain Termeer

Adrie Baselmans

Iris Ter Horst

Ina Klein Teeselink

Thijs Grunhagen

Raymond J Habets

Cornelis Willem Johannes Immanuel Spoel

Walter Everard Carels

Cornelis Willem Johannes Immanuël Spoel

Kirsten Helena Zuurmond

Raymond J E Habets

Maurice A Termeer

An apparatus for assessing a vessel of interest and a corresponding method are provided in which the modeling of the hemodynamic parameters using a fluid dynamics model can be verified by deriving feature values from the segmented vessel of interest and inputting these feature values into a classifier. The classifier may then determine, based on the feature values whether the segmentation has been performed from proximal to distal, from distal to proximal or cannot be determined from the provided data. An incorrect segmentation order can thus be identified and potentially be corrected, thereby avoiding inaccurate simulation results.

Orientation detection for 2D vessel segmentation for angio-FFR

A method for classifying a vasculature comprises training a training device with an initial model of a vasculature using diagnostic image data representing a geometry for a plurality of vessels of a vessel tree and including a respective vessel labeling for each vessel, providing at least one diagnostic image of a patient's vessel tree and identifying a variation between the vessel tree represented by the initial model and the patient's vessel tree. This variation is checked and labeled in order to improve the trained model. The process may be repeated iteratively until reaching an accurate patient-specific model of the vasculature.

Interactive coronary labeling using interventional x-ray images and deep learning

An apparatus for determining a functional index for stenosis assessment of a vessel is provided. The apparatus comprises an input interface () and a processing unit (). The input interface is configured to obtain image data () representing a two-dimensional representation of a vessel (). The processing unit () is configured to determine a course of the vessel () and a width (w, w) of the vessel along its course in the image data and is further configured to determine the functional index for stenosis assessment of the vessel based on the width of the vessel in the image data.

Apparatus for determining a functional index for stenosis assessment

The present invention relates to a device () for determining the position of stents () in an image of vasculature structure, the device () comprising: an input unit (); a processing unit (); and an output unit (); wherein the input unit () is configured to receive a sequence of images () of a vasculature structure () comprising at least one vessel branch (); wherein the processing unit () is configured to: detect positions of at least two markers () for identifying a stent position () in at least one of the images (); detect at least one path indicator () for the at least one vessel branch () in at least one of the images () of the vasculature structure () at least for vessel regions in which the positions of the markers () are detected; associate the at least two markers () to the at least one path indicator () based on the detected positions of the markers () and the location of the at least one path indicator (); assign markers () which are associated to the same path indicator () to a marker group to indicate a position () of at least one stent () in the vasculature structure (); and wherein the output unit () is configured to provide output data indicative of the positions of the markers () of the marker group. The invention provides a device and a method that improve the determination of the position of stents in complicated situations.

Device, system and method for determining the position of stents in an image of vasculature structure

An adaptive X-ray anti-scatter device for placement in a source-detector axis of an X-ray imager includes an anti-scatter filter having a source orientable surface and a detector orientable surface. The anti-scatter filter comprises a plurality of realignable slats that absorb incident X-rays and are separated by a plurality of interstitial portions. The device also includes a first actively deformable member comprising a first set of one or more actively deformable actuators disposed across a first region of the first actively deformable member. At least a portion of the first set is partially or fully recessed within the interstitial portions. At least one actuator of the first set is in contact with a corresponding realignable slat of the plurality of realignable slats and is configured to change the alignment of the corresponding realignable slat in relation to the source-detector axis.

Adaptive anti-scatter device

A method for classifying a vasculature comprises training a training device with an initial model of a vasculature using diagnostic image data representing a geometry for a plurality of vessels of a vessel tree and including a respective vessel labeling for each vessel, providing at least one diagnostic image of a patient's vessel tree and identifying a variation between the vessel tree represented by the initial model and the patients vessel tree. This variation is checked and labeled in order to improve the trained model. The process may be repeated iteratively until reaching an accurate patient-specific model of the vasculature.

Interactive coronary labeling using interventional X-ray images and deep learning

An apparatus for determining a functional index for stenosis assessment of a vessel is provided. The apparatus comprises an input interface () and a processing unit (). The input interface is configured to obtain image data () representing a two-dimensional representation of a vessel (). The processing unit () is configured to determine a course of the vessel () and a width (ww) of the vessel along its course in the image data and is further configured to determine the functional index for stenosis assessment of the vessel based on the width of the vessel in the image data.

The present invention relates to a device for interacting with vessel images, the device () comprising: an interface unit (); a processing unit (); wherein the interface unit () comprises: a display (); and an input setup (); wherein the display () is configured to display a vessel image (); wherein the input setup () is configured to receive a user input in relation to the vessel image (); wherein the processing unit () is configured to: determine, for at least one vessel () in the vessel image (), a vessel contour (); determine, from the user input, an identifier position () in the vessel image (); indicate at least a portion () of the vessel contour () in the vessel image (), if the determined identifier position () is spaced apart from the vessel contour () by a distance () within a predefined distance range; determine, from the user input, a drag direction (); and move the indicated portion () along the vessel contour () based on the determined drag direction ().

Device, system and method for interacting with vessel images

Vasculature modeling systems and methods are disclosed that generate an enhanced 3D model based on a combination of two dimensional, 2D, imaging data of a region of interest and 3D imaging data of the region of interest. A hemodynamic simulation is performed using the enhanced 3D model to derive at least one hemodynamic parameter based on the hemodynamic simulation.

Contrast injection imaging

In cardiac roadmapping, a 'roadmap', which is typically a representation of the vasculature of a patient obtained via previously acquired data from a CT scan, is overlaid on live intervention data, showing the position of an intervention device obtained using fluoroscopy. In this way, the intervention device may be tracked inside a realistic representation of the patient. The accurate registration of the fluoroscopic image to the roadmap data is an important step, otherwise the reported live position of the intervention device would not be shown at an accurate position inside the roadmap. Registration can be performed by the injection of contrast medium. In the case of cardiac roadmapping, the small vessel diameters mean that it is possible to register intervention devices directly. However, the behavior of intervention devices in larger vessels is difficult to predict, and so device-based registration is harder to achieve in such a context. By detecting the presence of a specific intervention device and a specific vascular context, an accurate registration of the intervention device to the 3D roadmap can be provided via comparison to a library of known device configurations.

Image registration

An apparatus for medical imaging of a patient, including an object of interest, is provided. The apparatus comprises a patient support unit, a processor, and a display. The patient support unit is configured to receive a patient. The processor is configured to receive scout images of the patient acquired in respective positions of the apparatus. Each respective position is represented by a position parameter. The processor is further configured to select at least one iso-centering image from the scout images by geometrical calculation using the position parameter of each scout image and a position parameter representing a present position of the apparatus. The processor is further configured to adapt the appearance of the at least one iso-centering image according to the present position of the apparatus. The display is configured to present the at least one adapted iso-centering image.

Iso-centering in C-arm computer tomography

An imaging apparatus images a first object (), like a tip of a catheter, disposed within a second object, such as a vascular structure of a person. A three-dimensional representation of the second object including a representation of a surface () of the second object and the position of the first object relative to the position of the second object are provided. A projection () of the first object onto the representation of the surface of the second object is determined and shown to a user like a physician on a display (). The three-dimensional spatial relationship between the first object and the second object is thereby shown in a way that is very native for the user, i.e. a visualization can be provided, which allows the user to easily and accurately grasp the three-dimensional spatial relationship between the first object and the second object.

Imaging apparatus for imaging a first object within a second object

The present invention relates to determining optimal C-arm angulation for heart valve positioning. In order to further improve the workflow in relation with the correct positioning of a valve prosthesis, it is described to provide () a 2D image of an aortic root of a heart of a patient, wherein the 2D image comprises three cusps of the heart in a visible and distinct manner. Further, 2D positions of the three cusps are indicated () in the 2D image. An analytical 3D model of the aortic cusp locations is provided (), and the 3D positions of the three cusps are computed () based on the 2D positions and the analytical 3D model. Still further, an optimal C-arm angulation is computed () based on the computed 3D positions of the cusps, wherein, in the optimal C-arm angulation, the three cusps are aligned in a 2D image. The optimal C-arm angulation is then provided for further image acquisition steps.

Determining C-arm angulation for valve positioning

The invention relates to an imaging device () for registration of different imaging modalities, an imaging system () for registration of different imaging modalities, a method for registration of different imaging modalities, a computer program element for controlling such device and a computer readable medium having stored such computer program element. The imaging system () for registration of different imaging modalities comprises a first imaging modality (), a second imaging modality (), and an imaging device () for registration of different imaging modalities. The imaging device () for registration of different imaging modalities comprises a model provision unit (), a first image data provision unit (), a processing unit (), a second image data provision unit (), and a registration unit (). The model provision unit () provides a cavity model of a visceral cavity. The first image data provision unit () provides first image data showing a region of interest of a patient by the first imaging modality (). The processing unit () registers the cavity model to the first image data and adapts the cavity model based on the first image data. The processing unit () differs between bony and non-bony structures and masks a non-bony structure in the first image data based on the adapted cavity model. The second image data provision unit () provides second image data showing the region of interest of a patient by the second imaging modality (). The registration unit () registers the masked first image data and the second image data.

Imaging device for registration of different imaging modalities

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Eindhoven, Netherlands

Javier Olivan Bescos