Koninklijke Philips Corporation N.v.

U.S. Philips Corporation

Philips Intellectual Property & Standards Gmbh

Rafael Wiemker

Thomas Buelow

Tobias Klinder

Martin Bergtholdt

Thomas Blaffert

Cristian Lorenz

Thomas Koehler

Daniel Bystrov

Axel Saalbach

Kirsten Regina Meetz

Jörg Sabczynski

Cornelis Petrus Hendriks

Joerg Sabczynski

Tim Philipp Harder

Tom Brosch

Steffen Renisch

Sven Kabus

Jens Von Berg

Heinrich Schulz

Jaap Roger Haartsen

Torbjorn Vik

Roland Johannes Opfer

Ingwer-Curt Carlsen

Michael Polkey

Stewart Young

Liran Goshen

Irina Waechter-Stehle

Harald Sepp Heese

Astrid Ruth Franz

Ingwer Curt Carlsen

Roberto Buizza

Vladimir Pekar

Klaus Erhard

Kiran Hamilton J Dellimore

Nicole Schadewaldt

Karsten Sommer

Torbjoern Vik

Kongkuo Lu

Sebastian Peter Michael Dries

Thorsten Manuel Buzug

Dominik Benjamin Kutra

Andre Goossen

Hrishikesh Narayanrao Deshpande

Mark Olszewski

Jorg Bredno

Roland Proksa

Jochen Peters

Hanns-Ingo Maack

Holger Schmitt

Michael Harald Kuhn

Gerhard Martens

Frank Michael Weber

Christopher Stephen Hall

Lilla Boroczky

Michael Kaus

Jochen Keupp

Fabian Wenzel

Claas Bontus

Ingmar Graesslin

Udo Van Stevendaal

Rolf Jürgen Weese

Hannes Nickisch

Shlomo Gotman

Andriy Yaroshenko

Manfred Mueller

Sheng Xu

Hans Barschdorf

Alexander Schmidt-Richberg

Heike Carolus

Matthias Lenga

Stefan Winter

Tanja Nordhoff

Nataly Wieberneit

Ewald Rössl

André Goossen, Sr

Heike Ruppertshofen

Lina Arbash Meinel

Martin Stahl

Sabine Dippel

Dominik Berjamin Kutra

Marten Bergtholdt

Rita Priori

Mukta Joshi

André GOOßEN

Karsten Rindt

A computer implemented method of making a measurement associated with a feature of interest in an image. The method comprises using () a model trained using a machine learning process to take the image as input and predict a pair of points between which to make the measurement of the feature of interest in the image. The method then comprises determining () the measurement, based on the predicted pair of points.

Making measurements in images

The present invention relates to multispectral imaging. In order to improve an identification of relevant multispectral material transitions (in particular caused by injected contrast agent), an apparatus is proposed to use the local maxima of the variances and/or covariances of the intensities of the multi-channel images to locate material transitions. In comparison to gradient vectors, the local variance is not directed and not prone to noise. An alternative apparatus is proposed to use the local covariance deficits of the intensities of the multi-channel images to locate material transitions. The proposed alternative approach is independent of spatial drifts across the image volume.

Local spectral-covariance or local spectral covariance deficits computation and display for highlighting of relevant material transitions in spectral CT and MR

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

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 method is provided for recording or representing captured ultrasound-derived information. The method is based on obtaining positioning information related to an ultrasound probe during execution of an ultrasound examination, and using this to associate captured data samples, or information derived therefrom, with anatomical position information for the data samples. The link between the two is achieved using an anatomical model which can relate probe surface position with anatomical body structure underlying the surface. A map can be generated of the obtained data as a function of position across the surface of the anatomical body. i.e. effectively a projection of the data onto the object 2D surface.

Method for use in ultrasound imaging

The invention refers to an apparatus () for generating an augmented image comprising a) a base image providing unit (), wherein the base image is generated based on a combination of spectral image data, b) a contrast image providing unit (), wherein the contrast image is generated based on a different combination of the spectral image data, c) a degree of saliency determination unit (), wherein the degree of saliency is indicative of a difference between an image value of a voxel of the contrast image and an image value of a corresponding voxel of a predetermined template image, and d) an augmented image generation unit () for generating an augmented base image of the object by augmenting voxels of the base image based on the degree of saliency. The invention allows to provide the augmented base image with an improved image quality and information content.

Apparatus for generating an augmented image of an object

A three-dimensional virtual endoscopy rendering of a lumen of a tubular structure is based on both non-spectral and spectral volumetric imaging data. The three-dimensional virtual endoscopy rendering includes a 2-D image of a lumen of the tubular structure from a viewpoint of a virtual camera of a virtual endoscope passing through the lumen. In one instance, the three-dimensional virtual endoscopy rendering is similar to the view which is provided by a physical endoscopic video camera inserted into the actual tubular structure and positioned at that location. The non-spectral volumetric image data is used to determine an opacity and shading of the three-dimensional virtual endoscopy rendering. The spectral volumetric image data is used to visually encode the three-dimensional virtual endoscopy rendering to visually distinguish an inner wall of the tubular structure and structure of interest on the wall.

3-D virtual endoscopy rendering

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 for reviewing a prior medical image and a related prior medical report, including: a plurality of measurement tools configured to: receive an input medical image and information regarding a medical finding; analyze the input medical image to determine a measurement relating to the medical finding; and output the measurement relating to the medical finding; a report analyzer configured to: receive the prior medical report; analyze the prior medical report to extract first information regarding a first medical finding described in the medical report; select a first measurement tool of the plurality of measurement tools to analyze the prior medical image based upon the first extracted information; and output the first extracted information to the first measurement tool, wherein the first measurement tool analyzes the prior medical image to produce a first updated measurement of the first medical finding and the first measurement tool analyzes a new medical image associated with the prior medical image to produce a new first measurement of the first medical finding; a report generator configured to receive the new first measurement and to produce a new report based upon the new first measurement.

Guided reviews of prior exams and reports

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

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

Presented are concepts for obtaining a confidence measure for a machine learning model. One such concept process input data with the machine learning model to generate a primary result. It also generate a plurality of modified instances of the input data and processes the plurality of modified instances of the input data with the machine learning model to generate a respective plurality of secondary results. A confidence measure relating to the primary result is determined based on the secondary results.

Confidence measure for a deployed machine learning model

A System for image processing (IPS), in particular for lung imaging. The system (IPS) comprises an interface (IN) for receiving at least a part of a 3D image volume (VL) acquired by PAT an imaging apparatus (IA) of a lung (LG) of a subject (PAT) by exposing the subject (PAT) to a first interrogating signal. A layer definer (LD) of the system (IPS) is configured to define, in the 3D image volume, a layer object (LO) that includes a representation of a surface (S) of the lung (LG). A renderer (REN) of the system (IPS) is configured to render at least a part of the layer object (LO) in 3D at a rendering view (V) for visualization on a display device (DD).

Image processing system and method

The invention relates to a system for assessing a pulmonary image which allows for an improved assessment with respect to lung nodules detectability. The pulmonary image is smoothed for providing different pulmonary images (20, 21, 22) with different degrees of smoothing, wherein signal values and noise values, which are indicative of the lung vessel detectability and the noise in these images, are determined and used for determining an image quality being indicative of the usability of the pulmonary image to be assessed for detecting lung nodules. Since a pulmonary image shows lung vessels with many different vessel sizes and with many different image values, which cover the respective ranges of potential lung nodules generally very well, the image quality determination based on the different pulmonary images with different degrees of smoothing allows for a reliable assessment of the pulmonary image's usability for detecting lung nodules. The image quality is used to determine a radiation dose level to be applied for generating a next pulmonary image.

System and method for assessing a pulmonary image

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Kisdorf, Germany

Rafael Wiemker