Koninklijke Philips Corporation N.v.

Fei Comapny

Paul Scherrer Institut

Koninklijke Philips Electronics N.v.

Philips Intellectual Property & Standards Gmbh

Thomas Koehler

Roland Proksa

Michael Grass

Ewald Roessl

Bernhard Johannes Brendel

Andriy Yaroshenko

Hanns-Ingo Maack

Gereon Vogtmeier

Heiner Daerr

Frank Bergner

Rafael Wiemker

Claas Bontus

Andy Ziegler

Rolf Dieter Bippus

Gerhard Martens

Tim Nielsen

Peter Forthmann

Axel Thran

Cornelis Petrus Hendriks

Holger Schmitt

Udo Van Stevendaal

Klaus Juergen Engel

Joerg Sabczynski

Kevin Martin Brown

Franz Pfeiffer

Jaap Roger Haartsen

Michael Polkey

Dirk Schaefer

Peter Koken

Dieter Geller

Peter Benjamin Theodor Noel

Roberto Buizza

Maximilian Von Teuffenbach

Franz Josef Pfeiffer

Herfried Karl Wieczorek

Cristian Lorenz

Sven Kabus

Kiran Hamilton J Dellimore

Jörg Sabczynski

Jens-Peter Schlomka

Ewald Rössl

Thomas Pralow

Peter Noel

Fabio De Marco

Lukas Benedict Gromann

Konstantin Willer

Bernardus Hendrikus Wilhelmus Hendriks

Levinus Pieter Bakker

Roger Steadman Booker

Tobias Klinder

Thomas Buelow

Jens Von Berg

Michael Harald Kuhn

Liran Goshen

Martinus Bernardus Van Der Mark

Robert Manzke

Ulrich Wolfgang Katscher

Dominic J Heuscher

Heinrich Schulz

Rolf Karl Otto Behling

Thomas Netsch

Drazenko Babic

Waltherus Cornelis Jozef Bierhoff

Klaus Erhard

Sven Prevrhal

Bernd R David

Walter Ruetten

Matthias Simon

Gilad Shechter

Johannes Wilhelmus Maria Jacobs

Antonius Maria Bernardus Van Mol

Harald Sepp Heese

Harold Agnes Wilhelmus Schmeitz

Hans-Aloys Wischmann

Tim Philipp Harder

Matthias Bertram

Sandeep Unnikrishnan

Bernd Menser

Marco Stampanoni

Dorothee Christine Hermes

Vishnu Vardhan Pully

Andre Goossen

Hrishikesh Narayanrao Deshpande

Tanja Nordhoff

Stefan Winter

Nataly Wieberneit

Zhentian Wang

Christiaan Kok

Klaus Jürgen Engel

Ingwer-Curt Carlsen

Marco Andreas Jacobus Van As

Franciscus Marinus Antonius Maria Van Gaal

Jon Erik Fredenberg

Bernd Lundt

Ronny Ziegler

Paulus René Maria Van Beers

Daniela Muenzel

Colas Schretter

Matthias Teders

A method for use in a material decomposition procedure applied to dual-energy CT projection data. Material decomposition is often done using pre-computed lookup tables (LUTs) for mapping input projection data, acquired with particular X-ray source parameters, to material data values. However, the X-ray source parameters can vary over the course of a scan, making the results inaccurate. Embodiments are based on determining in advance a plurality of sets of basis LUTs for each of a plurality of different possible ranges of values over which the X-ray source parameter may vary during a scan. The basis LUTs in each set are devised as being LUTs which represent the majority contribution to the overall material decomposition function for the time-varying energy spectrum. When performing a material decomposition procedure, an appropriate set of the basis LUTs is chosen, based on an identified range of variation of the X-ray source parameter during the scan, and a linear combination of the basis LUTs is defined, using weightings which depend upon instantaneous values of the X-ray source parameter during the scan period.

Method for improving ct-based material decomposition

The present invention relates to a device () and related method and computer-program product for planning an acquisition by a CT scanner (). The device receives a pre-scan image of the object from the scanner via an input (). A processor (), in use of the device, obtains a parameter selection based on the pre-scan image, in which this parameter selection comprises at least axial upper and lower scan range limits of a region of the object to be scanned. The processor determines a value indicative of an image gradient or gradient component in the pre-scan image at the upper and/or lower scan range limit or in a predetermined neighborhood thereof. If this value exceeds a threshold, a user is informed via an output () that the selected scan range does not satisfy a quality criterium for reconstruction and/or a new parameter selection is determined by repositioning, resizing and/or changing an orientation of the selected region to be scanned.

Planning of wide-coverage axial CT scans

A computed tomography imaging system () includes an X-ray radiation source () configured to emit X-ray radiation that traverses an examination region () and an X-ray radiation sensitive detector array () configured to detect X-ray radiation traversing the examination region and generate a view of line integrals. The imaging system further includes a subject support table top () configured to translate in the examination region for a scan based on at least one scan parameter. The imaging system further includes an operator console (), which includes a processor () and computer readable storage medium () with a scan parameter adapter module (). The processor is configured to execute instructions of the scan parameter adapter module, which causes the processor to determine a contrast agent concentration from the view of line integrals and adjust the at least one scan parameter based on the determined concentration.

Scan parameter adaption during a contrast enhanced scan

An intubation assistance device includes an electronic controller configured to: identify, from one or more images of a patient, information about the patient including at least a diameter of a trachea and a length of an intubation pathway; determine a recommended ETT size including an ETT diameter and an ETT depth of insertion from the determined diameter of the trachea and the determined length of the intubation pathway; and display the recommended ETT size on a display device.

Imaging-based sizing optimization of endotracheal tube for mechanical ventilation

An apparatus () for use in conjunction with a medical imaging device () having an imaging device controller () that displays a graphical user interface (GUI) () including a preview image viewport (). The apparatus includes at least one electronic processor () programmed to: receive a video feed () of the GUI displayed on the imaging device controller; extract a preview image () displayed in the preview image viewport from the live video feed of the GUI; perform an image analysis () on the extracted preview image to detect one or more image features () indicative of one or more potential problems associated with a medical imaging examination performed with the medical imaging device; and output an alert () when one or more potential problems associated with the medical imaging examination is detected from the one or more image features.

Instant scout scan checker

Concepts for multi-energy dark-field (DAX) and phase-contrast (PC) X-ray imaging are proposed. One such concept comprise acquiring a set of low energy images with phase stepping and a set of high energy images (with or without phase stepping). Transmission, DAX, and PC images are obtained from the phase-stepped low energy images using phase retrieval. Also, a high energy transmission image is obtained from the high energy image(s). Based on the transmission image from the low energy images and the transmission image from the high energy image(s), a modified transmission image is generated.

X-ray imaging system and method

This invention relates to an image processing device () comprising an input () for receiving image data representative of a region of interest in the body of a patient from a medical X-ray imaging apparatus (). The image data comprises a first dark-field image obtained for a first X-ray spectrum and a second dark-field image obtained for a second, different. X-ray spectrum. A combination unit () provides a combination image that is representative of a medical condition map. e.g. a lung condition map, by combining the first dark-field image and the second dark-field image.

Spectral dark-field imaging

A diaphragm measurement device includes at least one electronic processor programmed to perform a diaphragm measurement method including receiving ultrasound imaging data of a dimension of a diaphragm of a patient during inspiration and expiration while the patient undergoes mechanical ventilation therapy with a mechanical ventilator; receiving respiratory data of the patient during inspiration and expiration while the patient undergoes the mechanical ventilation therapy; calculating a diaphragm thickness metric based on the received ultrasound imaging data of the diaphragm of the patient and the received respiratory data; and displaying, on a display device, a representation of the calculated diaphragm thickness metric.

Accurate diaphragm thickness and function evaluation using ultrasound and mechanical ventilator signals

A non-transitory storage medium stores instructions readable and executable by at least one electronic processor to receive clinical data for a current patient (P); search a database of CT scans and/or patient-specific mechanical ventilation models for other patients using the clinical data for the current patient as a search criterion to identify a similar patient in the database and similar patient data (S) comprising a CT scan and/or a patient-specific mechanical ventilation model for the similar patient; determine a patient-specific mechanical ventilation model for the current patient based on the CT scan and/or patient-specific mechanical ventilation model for the similar patient; generate ventilator configuration data for mechanically ventilating the current patient based on the determined patient-specific mechanical ventilation model for the current patient.

Mechanical ventilator configuration for mechanical ventilation of a patient with limited or no imaging data of the patient

A mechanical ventilation device comprising at least one electronic controller is configured to receive images of lungs of a patient undergoing mechanical ventilation therapy with a mechanical ventilator, the images being acquired over time and having timestamps; process the images to generate timeline images at corresponding discrete time points; and display a timeline of the timeline images on a display device.

Inter- and extrapolation of chest image and mechanical ventilation settings into a time lapse series for progression monitoring and outcome prediction during long term mechanical ventilation

A system (IPS) and related method for image processing, in particular dark-field or phase contrast imaging to reduce motion artifacts. The system comprises an input interface (IN) for receiving a series of projection images (π) acquired by an X-ray imaging apparatus (XI) of an object (OB) for a given projection direction, the imaging apparatus (XI) configured for phase-contrast and/or dark-field imaging A phase-contrast and/or dark-field image generator (IGEN) applies an image generation algorithm to compute a first image based on the series the projection images (π). A motion artifact detector (MD) detects a motion artifact in the first image. A combiner (Σ) combines, if a motion artifact is so detected, a part of the first image with a part of at least one auxiliary image to obtain a combined image. The auxiliary image was previously computed by a gated application of the image generation algorithm in respect of a subset of the series of the projection images (π). The combined image may be output at an output interface (OUT) as a motion artifact reduced image.

System and method for correcting motion artifacts by combining images in phase-contrast and dark-field imaging applications

An intubation assistance device includes an electronic controller configured to: generate a patient respiratory tract geometry model of at least a portion of a human respiratory tract by inputting one or more patient variables into a statistical shape model (SSM) of at least a portion of the human respiratory tract; select a recommended endotracheal tube (ETT) size by modeling at least one ETT model inserted into the patient respiratory tract geometry model to form a virtual fit model and estimating at least one fit parameter based on the virtual fit model; and display the recommended ETT size on a display device.

Endotracheal tube size selection and insertion depth estimation using statistical shape modelling and virtual fitting

A focusing grating device () is described comprising a substrate () and a grating comprising a plurality of grating features () positioned on the substrate (). The grating features () are positioned non-perpendicular to the substrate surface, thereby inducing a first focusing direction. The substrate () is curved, thereby inducing a second focusing direction, which is different from the first focusing direction. An X-ray system () comprising such a focusing grating device () as well as a method for producing such a focusing grating device () are also described.

Focusing grating devices with large aspect ratio

The present invention relates to a calculation device () for comparing dark-field X-ray images. The calculation device in () is configured for receiving a first dark-field X-ray image () describing first dark-field X-ray signals of a patient at an expiration state and for receiving a second dark-field X-ray image () describing second dark-field X-ray signals of the patient at an inspiration state. The calculation device is further () configured for normalizing the first dark-field X-ray signals of the first dark-field X-ray tin image () with a lung thickness value describing the lung thickness at the expiration state and for normalizing the second dark-field X-ray signals of the second dark-field X-ray image () with a lung thickness value describing the lung thickness at the inspiration state. Further, the calculation device () is configured for comparing the normalized first dark-field X-ray signals with the normalized second dark-field X-ray signals, thereby determining a comparison result () and for determining whether at least one area of the patient's lung with a ventilation defect exists based on the comparison result ().

Calculation device for determining ventilation defects

The present invention relates to the use of dark field X-ray images in an ablation treatment of a tumour. By acquiring dark field X-ray images displaying the region of interest targeted in the ablation treatment, information can be derived which allows taking a decision on terminating the ablation treatment. A set of dark field X-ray images is received (), which is acquired at different time instants and comprises the region of interest. Dark field X-ray images of the set are compared (), for example by determining difference images between the individual images. If during that comparison a change in the dark field X-ray images is detected over time in the region of interest, then a signal is generated () indicating a change has occurred. That signal may indicate that healthy tissue is being affected instead of the tumour and that consequently the ablation treatment should be ended.

Device and method for evaluating dark field images

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Norderstedt, Germany

Thomas Koehler