Koninklijke Philips Corporation N.v.

Philips Lighting Holding B.v.

Koninklike Philips N.v.

Signify Holding B.v.

Koninklijke Philips Electronics N.v.

Ruud Vlutters

Karl Catharina Van Bree

Frederik Jan De Bruijn

Dmitry Nikolayevich Znamenskiy

Lorenzo Feri

Bin Yin

Remco Theodorus Johannes Muijs

Franciscus Hendrikus Van Heesch

Harold Agnes Wilhelmus Schmeitz

Vincent Jeanne

Pierre Hermanus Woerlee

Ronald Rietman

Reinhold Wimberger-Friedl

Tim Corneel Wilhelmus Schenk

Antonia Cornelia Van Rens

Anke Pierik

Giovanni Cennini

Marinus Bastiaan Van Leeuwen

Wilhelmus Robert Koppers

Dmitry Nikolaevich Znamenskiy

Dmitri Anatolievich Chestakov

Johannes Joseph Hubertina Barbara Schleipen

Hubert Cécile François Martens

Tommaso Gritti

Adrienne Heinrich

Ronald Reindert Drenten

Rudolf Maria Jozef Voncken

Bas Hulsken

Jelte Peter Vink

Tim Schenk

Fei Zuo

Hong Liu

Sieglinde Neerken

Mark Van Schijndel

Octavian Soldea

Tim Corneel Wilhel Schenk

Frits De Bruijn

Danielle Elisa Willemine Clout

Deep Bera

Frederik J De Bruijn

A process for converting an arbitrary input digital pathology image into an output digital pathology image that shares statistical information with a reference image. The input digital pathology image is separated into two or more image sections. Each image section is encoded, using a first convolutional neural network, into one or more feature maps. The one or more feature maps of each image section are modified based on statistical information derived from a reference image. The modified feature map(s) of each image section is/are then decoded to construct a respective image section for an output image. The constructed image sections for an output image then form the output image.

Planning radiation therapy using a personalized hematologic risk score

Disclosed is a system for analysis of microscopic image data which includes a data processing system. Pixel classification data for each of a plurality of pixels of the microscopic image data are read. The pixel classification data include for each of the pixels of the microscopic image data, binary or probabilistic classification data for classifying the pixel of the microscopic image data into one or more object classes of pre-defined objects which are shown by the image. At least a portion of the pixels of the microscopic image data are grouped to form one or more pixels groups. For each of the pixel groups, probabilistic group classificati on data are calculated depending on the pixel classification data of the pixels of the respective group. The probabilistic group classification data are indicative of a probability that the group shows at least a portion of an object of the respective object class.

System and method for analysis of microscopic image data and for generating an annotated data set for classifier training

The invention relates to a respiratory motion detection apparatus () for detecting respiratory motion of a person. An illuminator () illuminates the person () with an illumination pattern (), and a detector () detects the illumination pattern () on the person () over time. A temporal respiratory motion signal being indicative of the respiratory motion of the person () is determined from the detected illumination pattern by a respiratory motion signal determination unit (). The illumination pattern deforms significantly with slight movements of the person. Thus, since the respiratory motion signal determination unit () is adapted to determine the temporal respiratory motion signal from the detected illumination pattern, even slight respiratory movements of the person can be determined. The sensitivity of detecting respiratory movements of a person can therefore be improved.

Respiratory motion detection apparatus

The invention relates to a printing control device () to control printing of a cover layer on a tissue or cell sample to be examined, a system () for printing of a cover layer () on a tissue or cell sample to be examined, a method to control printing of a cover layer on a tissue or cell sample to be sample to be examined, a computer program element for controlling such device or system for performing such method and a computer readable medium having stored such computer program element. The printing control device () comprises an imaging unit () and a printing control unit (). The imaging unit () is configured to provide image data of the sample, and to determine a local image parameter from the image data. The local image parameter relates to local tissue porosity and/or a local capillary force of the sample. The printing control unit () is configured to control a printing parameter for printing the cover layer on the sample based on the local image parameter.

Printing control device to control printing of a cover layer on a sample

The present invention relates to an illustration of an annotation () at a sample slide (). It is the intention for the invention to copy the annotation () provided at a reference slide () to the sample slide (). Typically, a reference image () of the reference slide () is provided, in particular by scanning the reference slide (). The reference image () therefore has the information about a reference slice () which is carried by the reference slide (). Furthermore, the reference slide () has been marked with a region of interest () and the annotation (), which can be associated with the region of interest (). If such reference slide () is scanned, the respective reference image () comprises the information about the marked region of interest () as well as the annotation (), too. Furthermore, the sample slide () carrying a sample slice () can be scanned, in order to provide a sample image (). The sample slice () and the reference slice () are cut from the same object () of a biological material. In particular, the sample slice () has been cut directly after a cut of a material block has been preformed to provide the reference slice (). Since the reference slice () and the sample slice () are from the same object (), their features are very likely that the reference image () and the sample image () are very similar. Due to this similarity, the annotation () of the reference slide () is copied on a basis of an image recognition between reference image () and the sample image () to the sample slide ().

Information transformation in digital pathology

A method for estimating the absolute size dimensions of a test object based on image data of the test object, namely a face or part of a person. The method includes receiving image data of the test object, determining a first model of the test object based on the received image data, and aligning and scaling the first model to a first average model that includes an average of a plurality of first models of reference objects being faces or parts of faces of reference persons. The first models of the reference objects are of a same type as the first model of the test object. The method further includes determining a shape difference between the test object and an average of the reference objects, determining a second model of the test object with an estimated scale based on (i) the determined shape difference, (ii) a statistical operator that is indicative of a statistical correlation between shape and size dimensions of the reference objects, and (iii) a second average model, and determining the size dimensions of the test object based on the second model of the test object.

Method and device for estimating obsolute size dimensions of test object

An electronic apparatus () including a display generation unit () configured to generate a display area () in a user interface, the display area being configured to display a 3-D model of a patient's face and a 3-D model of a patient interface device fitted to the 3-D model of the patient's face; and an interaction map unit () configured to generate an interaction map tool () in the user interface and to calculate an interaction map between the patient's face and the patient interface device indicating levels of an interaction characteristic between the patient's face and the patient interface device, wherein the interaction map tool is operable to toggle display of the interaction map in the user interface.

Patient interface device selection system and method based on three-dimensional modelling

A system () including a geometric fit score database () configured to store a plurality of 3-D models of faces and a pre-calculated geometric fit score for each of one or more patient interface devices for each of one or more of the faces, and a first processing unit () including a match finding unit () configured to match the 3-D model of the patient's face with one or more of the stored 3-D models of faces and to use the pre-calculated geometric fit score for each of the one or more of the patient interface devices for the one or more matched faces to determine the geometric fit score for each of the one or more patient interface devices for the patient's face.

3D patient interface device selection system and method

A series of structured lighting patterns are projected on an object. Each successive structured lighting pattern has a first and second subset of intensity features such as edges between light and dark areas. The intensity features of the first set coincide spatially with intensity features from either the first or second subset from a preceding structured lighting pattern in the series. Image positions are detected where the intensity features of the first and second subset of the structured lighting patterns are visible in the images. Image positions where the intensity features of the first subset are visible are associated with the intensity features of the first subset, based on the associated intensity features of closest detected image positions with associated intensity features in the image obtained with a preceding structured lighting pattern in said series. Image positions where the intensity features of the second subset are visible, between pairs of the image positions associated with intensity features of the first subset, with intensity features of the second subset between the intensity features associated with the pair of positions. The associated intensity features in a final structured lighting pattern of the series are used to identify the intensity features of the final structured lighting pattern for the determination of 3D surface position information.

3D scanner using structured lighting

The present invention relates to a scanning device (') for scanning an object (), wherein the scanning device () comprises a projection unit () for projecting an alignment image () onto the object (), said alignment image () comprising a main pattern (), an image capturing unit () for capturing a live camera image () of the object (), said live camera image () comprising a derivative pattern () of the main pattern (), the derivative pattern () representing said projected alignment image () as seen from the image capturing unit viewpoint, and an alignment unit (&#x2032;) for providing an indication of a correct position and/or orientation of the scanning device () with respect to the scanned object () on the basis of the captured live camera image ().

Scanning device and method for positioning a scanning device

An electronic apparatus for use in selecting a patient interface device and including a geometric fit score determining unit () configured to calculate a geometric fit score for each of one or more of patient interface devices, a patient criteria fit score determining unit () configured to calculate a patient criteria fit score for each of the one or more patient interface devices, and an overall fit score determining unit () configured to calculate an overall fit score for each of the one or more patient interface devices based on the calculated geometric fit score and the calculated patient criteria fit score for each of the one or more patient interface devices.

There is provided a light detection system which is capable of determining in light embedded codes by detecting light in a scene which is illuminated by an illumination system () comprising one or more light sources () each providing a light contribution (I, I, I) comprising an embedded code (ID#1, ID#2, ID#3) emitted as a temporal sequence of modulations in a characteristics of the light emitted. The light detection system comprises light detection means (), which are arranged for acquiring at least one image of the scene, where the image is acquired a plurality of temporal shifted line instances. Each line of the acquired image comprises an instance of the temporal sequence of modulations of the first embedded code. The light detection system further comprises means () for determining embedded codes from the spatial pattern of modulations.

Light detection system and method

An electronic apparatus () includes a display generation unit () configured to generate a display area () in a user interface (--), the display area being configured to display a 3-D model of a patient's face and a 3-D model of a patient interface device fitted to the 3-D model of the patient's face; and a transparency adjustment unit () configured to generate a transparency adjustment tool () in the user interface, the transparency adjustment tool being operable to adjust the transparency of a subset of components of the 3-D model of the patient interface device displayed in the 3-D display area of the user interface.

3D modeled visualisation of a patient interface device fitted to a patient's face

The location of a face is detected from data about a scene. A 3D surface model from is obtained from measurements of the scene. A 2D angle data image is generated from the 3D surface model. The angle data image is generated for a virtual lighting direction, the image representing angles between a ray directions from a virtual light source direction and normal to the 3D surface. A 2D face location algorithm is applied to each of the respective 2D images. In an embodiment respective 2D angle data images for a plurality of virtual lighting directions are generated and face locations detected from the respective 2D images are fused.

Face location detection

The present invention provides a cost effective customization of user interface devices for use with respiratory ventilation systems, such as face masks that may be used for CPAP therapy. By integrating a user specific customize element () into a pre-fabricated user interface device (), increased comfort for a user during use of the interface device () is provided. The customized element () is adapted to affect the shape of the user interface device making it compliant with at least one user specific body feature, for example, a facial feature of a particular user. The shape of the customized element may be computed from a user specific data set representing an e.g. three-dimensional shape at least one body feature of a user.

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Eindhoven, Netherlands

Ruud Vlutters