Koninklijke Philips Corporation N.V.

Koninklijke Philips Electronics N.v.

Philips Intellectual Property & Standards Gmbh

Stewart Young

Jens Von Berg

Daniel Bystrov

Thomas Buelow

Thomas Netsch

Kirsten Regina Meetz

Fabian Wenzel

Nataly Wieberneit

Vladimir Pekar

Ingwer Curt Carlsen

Rafael Wiemker

Heinrich Schulz

Tim Philipp Harder

Sven Kroenke

Michael Kaus

Axel Saalbach

Frank Olaf Thiele

Tanja Nordhoff

Biswaroop Chakrabarti

Arianne Van Muiswinkel

Soubhik Paul

Prasad Adhikarath Valappil

Ralph Buchert

Sven Krönke

Michael Grass

Raoul Florent

Ewald Roessl

Juergen Weese

Michael Harald Kuhn

Christopher Stephen Hall

Lyubomir Georgiev Zagorchev

Joerg Sabczynski

Pallavi Vajinepalli

Tom Brosch

Claire Levrier

Hans Barschdorf

Heike Carolus

Ulrich Neitzel

Johan Michiel Den Harder

Dominik Benjamin Kutra

Hrishikesh Narayanrao Deshpande

Sudipta Chaudhury

André Goossen, Sr

Bernd Lundt

Thomas Rohse

Christian Adrian Cocosco

Jan-Hendrik Buhk

Sven Kroenke-hille

Kirsten Meetz

Cornelis Johannes Fransiscus Maria Bergmans

Torjoern Vik

Lyubomir Georglev Zagorchev

Heiner Matthias Brueck

Benjamin Hawellek

Christina Textor

Christopher Brian Martel

Michael Kuhn

Ingwer C Carlsen

There is provided a computer-implemented method for determining rotation of a patient's chest in a medical image. The method comprises: receiving the medical image of the patient; processing the medical image to determine scapular spatial data relating to the patient's scapula; and determining rotation of the patient's chest with respect to at least one reference axis using the scapular spatial data.

Determining rotation of a patient's chest in a medical image

When performing an imaging scan on a patient, x-ray tube currents are modulated as the scan is performed. The x-ray tube current values and modulations may be recorded and accessed. The accessed values may be processed to generate overlays and displays for identifying patient and diagnostic device issues.

Systems and methods for processing and visualizing tube current modulations in medical imaging devices

A computer-implemented method for positioning a subject in medical imaging, comprising: receiving a first image () of a region of interest () of the subject (S); determining first positioning data based on the first image (), wherein the first positioning data indicates an alignment of the region of interest () relative to a first image acquisition unit used to acquire the first image () (S); determining guidance data based on the first positioning data, wherein the guidance data comprises a guidance for an alignment of the region of interest () relative to a second image acquisition unit used to acquire a second image () from a current alignment to a target alignment, wherein the target alignment is to correspond to that derived from the first positioning data (S); providing the guidance data for acquiring the second image () (S).

Guidance for positioning a patient in medical imaging

An orientation of a patient's chest is determined by an apparatus and method. According to the invention, a camera image of a patient comprising image data of the patient's chest is received, wherein the camera image is acquired with an optical camera. Further, an X-ray radiograph of the patient's chest with an X-ray imaging axis extending from an X-ray source to an X-ray detector is received. Then, the camera image and the X-ray radiograph are provided to at least one processor. Further, information relating to a clavicle to spinous process distance of the patient is then determined using the camera image. Finally, an orientation of the patient's chest in the X-ray radiograph with respect to the X-ray imaging axis is determined using the camera image, the X-ray radiograph, and the information relating to the clavicle to spinal process distance of the patient.

Apparatus for determining an orientation of a patient's chest

In a conventional system for preparing reports on findings in medical images, the actual formulation of the report is not or only insufficiently supported by the computer-based system. Although there are efforts to improve such a system through automatic reporting, however, in previous systems, the error rate is too high and/or the operation of the system too complicated. This application proposes to provide text prediction to a user on the display device. The text prediction is based on prior analyzing the image content of a medical image at is displayed to the user at least when the user activates a text field shown on the display device via the input unit. The displayed text prediction is selected from a pre-defined set of text modules that are associated to the analysis result.

Automatic diagnosis report preparation

The present invention relates to landmark and/or temporal event detection. It is proposed to utilize previously learned spatial statistical correlations between multiple landmarks in order to regularize convolutional neural networks (CNNs) either as a post-processing step or during training in order to utilize anatomical prior knowledge, reduce the false-positive prediction rate, and/or increase the accuracy and stability of the algorithm. The proposed apparatus and method may also be applied to improve the detection of correlated events in e.g., time-series by leveraging prior knowledge.

Probabilistic regularization of convolutional neural networks for multiple-feature detection based on correlations

An apparatus () for manually auditing a set () of images having quality ratings () for an image quality metric assigned to the respective images of the set of images by an automatic quality assessment process () includes at least one electronic processor () programmed to: generate quality rating confidence values () indicative of confidence of the quality ratings for the respective images; select a subset () of the set of images for manual review based at least on the quality rating confidence values; and provide a user interface (UI) () via which only the subset of the set of images is presented and via which manual quality ratings () for the image quality metric are received for only the subset of the set of images.

Workload reducer for quality auditors in radiology

The present invention relates to an X-ray imaging system (), comprising: an X-ray image acquisition unit (); and a processing unit (). The processing unit is configured to instruct the X-ray image acquisition unit to carry out a sequence of scans of a body part of a patient. The X-ray image acquisition unit is configured to provide the processing unit with an X-ray image of the body part for a scan of the sequence of scans. The processing unit is configured to determine that the scan needs to be repeated, wherein the determination comprises analysis of the X-ray image of the body part. The processing unit is configured to determine that an action other than acquisition of the next scan in the scan sequence is required, wherein the determination comprises analysis of the X-ray image of the body part. The processing unit is configured to determine that the X-ray imaging unit is required to carry out the next scan in the scan sequence based on a determination that the scan does not need to be repeated and that an action other than acquisition of the next scan in the scan sequence is not required.

X-ray imaging system

In order to enhance enhanced X-ray image inhalation quality monitoring, a metric is proposed hat reproducibly provides an index of ribs visible to be used in the assessment of the inhalation state. In an example, a detected diaphragm in a chest X-ray image may be projected into an atlas that contains labels for all intercostal spaces, namely spaces between rib centerlines. A spatial representation of both the clavicle and the ribs is provided in the atlas, a cumulative histogram is built for all points, i.e. pixels, of the diaphragm, for every point a rib label counter of the rib in the rib label map at that point is incremented as well as all ribs above it, the rib label counter is normalized by a division by the number of points, the median (or a different quantile) may be taken of this distribution serving as an inhalation index. An objective metric of inhalation state is thus achieved.

Inhalation metric for chest x-ray images

The invention relates to a method () for supervised training of an artificial neural network for medical image analysis. The method comprises acquiring (SI) first and second sets of training samples, wherein the training samples comprise feature vectors and associated predetermined labels, the feature vectors being indicative of medical images and the labels pertaining to anatomy detection, to semantic segmentation of medical images, to classification of medical images, to computer-aided diagnosis, to detection and/or localization of biomarkers or to quality assessment of medical images. The accuracy of predetermined labels may be better for the second set of training samples than for the first set of training samples. The neural network is trained (S) by reducing a cost function, which comprises a first and a second part. The first part of the cost function depends on the first set of training samples, and the second part of the cost function depends on a first subset of training samples, the first subset being a subset of the second set of training samples. In addition, the second part of the cost function depends on an upper bound for the average prediction performance of the neural network for the first subset of training samples and the second part of the cost function is configured for preventing that the average prediction performance for the first subset of training samples exceeds the upper bound.

Constrained training of artificial neural networks using labelled medical data of mixed quality

The field of view of an X-ray imaging system should be set appropriately to ensure that anatomical information of interest is not omitted. In particular, it is necessary to ensure that the operator of an X-ray system does not allow a patient to leave the X-ray imaging system until it is certain that the correct anatomy has been imaged. This application discusses a technique enable the visualization of a field of view boundary error caused by the incorrect configuration of an X-ray imaging system. Optionally, the boundary error is displayed either on a user display of a system console, or by projecting the field of view error onto the patient in the X-ray system. Thus, an operator of the system may be alerted to the presence of a boundary error, enabling a new X-ray exposure to be taken, if necessary.

Visualizing collimation errors

Medical radiography requires specialist control of radiography equipment to achieve good imaging results. Typical errors that can occur consist of an inappropriate field of view being accidentally applied. This results in a 'cropping effect' in which portions of the region of interest of a patient which would be of clinical use are omitted from the image. Conventionally, the only solution is to re-take the entire image with a more appropriate (and inevitably larger) field of view selected. This is undesirable, because it might require recall of the patient from another location, and the patient will be subject to two exposures, thus undesirably increasing their X-ray dosage. The present application proposes to use an anatomical atlas to analyse an X-ray image output from an initial exposure, in particular to assess whether significant anatomical elements are missing from the image. If elements are missing, the field of view of the X-ray imager is recalibrated, using collimation or pan/tilt adjustments, for example. A subsequent X-ray image is obtained, and combined with the initial image, to provide an output image. Because only a small area of the region of interest may subsequently need to be exposed, a smaller additional dose results.

X-ray apparatus having a composite field of view

The present invention relates to an apparatus for the detection of opacities in X-ray images. It is described to provide () an analysis X-ray image of a region of interest of an analyzed body part. A model of a normal region of interest is provided (), wherein the model is based on a plurality of X-ray images of the region of interest. At least one abnormality is detected () in the region of interest of the analyzed body part, the detection comprising comparing the analysis X-ray image of the region of interest and the model of the normal region of interest. Information is output () on the at least one abnormality.

Apparatus for the detection of opacities in X-ray images

The present invention relates to a device and method for quality assessment of medical image datasets. To enable an automatic quality assessment of medical image datasets to identify potential errors or deviations that may be avoided in future imaging operations, the device comprises an image input () for obtaining medical image datasets together with respective acquisition information, each medical image dataset being acquired by scanning a field of view, FOV, of an examination object and the respective acquisition information representing information related to the acquisition of the respective medical image dataset; an image analysis unit () for comparing the FOV of an obtained medical image dataset with a reference FOV and for determining difference information indicating deviations of the FOV from the reference FOV; a correlation unit () for determining correlation information indicating correlations between the difference information determined for a plurality of obtained medical image datasets and the respective acquisition information; and an output unit () for issuing the determined correlation information.

Device and method for quality assessment of medical image datasets

The present invention relates to device, system and method for verifying image-related information of a medical image. In order to assure the correctness of the image-related information of the medical image the device comprises an image input () for obtaining a medical image and associated image-related information, a translator () for translating one or more pieces of image-related information into expected anatomical feature information, a detector () for searching the expected anatomical feature information in the obtained medical image or for detecting one or more given anatomical features in the obtained medical image and comparing them with the expected anatomical feature information, an evaluator () for evaluating the result of the detector to generate a consistency measure indicating the consistency of the image-related information with the associated medical image, and an output interface () for outputting an inconsistency indication if the generated consistency measure is lower than a predetermined consistency threshold.

Device, system and method for verifying image-related information of a medical image

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Hamburg, Germany

Stewart Young