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公开(公告)号：US20200043616A1
公开(公告)日：2020-02-06
申请号：US16469334
申请日：2017-12-06
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： AXEL SAALBACH , TIM PHILIPP HARDER , TANJA NORDHOFF , RAFAEL WIEMKER , FABIAN WENZEL , JENS VON BERG , IRINA WAECHTER-STEHLE
Abstract: A system includes an analytics unit (140), which compares a medical image (105) and associated information with a stored medical guideline (142), and identifies an error or a deviation (340) from the medical guideline based on the comparison.
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公开(公告)号：US20180025546A1
公开(公告)日：2018-01-25
申请号：US15513184
申请日：2015-09-18
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： THOMAS BUELOW , DANIEL BYSTROV , RAFAEL WIEMKER , DOMINIK BENJAMIN KUTRA
CPC classification number: G06T19/20 , G06F19/321 , G06T19/00 , G06T19/003 , G06T2219/008
Abstract: A system and method is provided for visualizing a volumetric image of an anatomical structure. Using a first view of the volumetric image showing a non-orthogonal cross-section of a surface of the anatomical structure, a local orientation of the surface within the volumetric image is determined, namely by analyzing the image data of the volumetric image. Having determined the local orientation of the surface, a second view is generated of the volumetric image, the second view being geometrically defined by a viewing plane intersecting the surface of the anatomical structure in the volumetric image orthogonally. Accordingly, the surface is shown in a sharper manner in the second view than would typically be the case in the first view. Advantageously, the user can manually define or correct a delineation of the outline of the anatomical structure in a more precise manner. Moreover, various other advantageously uses of such a second view exist, such as facilitating the image interpretation by the clinician, more reliable further automatic analysis, etc.
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公开(公告)号：US20140330119A1
公开(公告)日：2014-11-06
申请号：US14334176
申请日：2014-07-17
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： THOMAS BUELOW , RAFAEL WIEMKER , CRISTIAN LORENZ , STEFFEN RENISCH , THOMAS BLAFFERT
IPC: G06T7/00
CPC classification number: G06T7/0012 , A61B6/032 , A61B6/481 , A61B6/5217 , G06T5/50 , G06T7/10 , G06T7/12 , G06T7/149 , G06T2207/10081 , G06T2207/10116 , G06T2207/30061 , G06T2207/30064 , G06T2207/30101
Abstract: An imaging method for identifying abnormal tissue in the lung is provided, comprising the recording of slice images of the lung by means of X-ray radiation, recording of blood vessels, differentiation of blood vessels and abnormal tissue, segmentation of the abnormal tissue and display of the segmented abnormal tissue on an output device. In addition, a computer tomograph for identifying abnormal tissue in the lung is provided, having a radiation source for recording slice images of the lung and blood vessels by means of X-ray radiation, a computer unit for differentiating the blood vessels from the abnormal tissue and for segmenting the abnormal tissue, as well as an output device for displaying the segmented abnormal tissue. Furthermore, a computer program is provided for controlling a computer tomograph for an identification of abnormal tissue in the lung by means of a radiation source, designed to record slice images of the lung and blood vessels by means of X-ray radiation, to differentiate the blood vessels from abnormal tissue, to segment the abnormal tissue and to control an output device for displaying the abnormal tissue.
Abstract translation: 提供了一种用于鉴定肺中异常组织的成像方法，包括通过X射线照射记录肺的切片图像，记录血管，血管和异常组织的分化，异常组织的分割和显示 的输出装置上的分段异常组织。 另外，提供了一种用于识别肺中的异常组织的计算机断层摄影机，具有用于通过X射线辐射记录肺和血管的切片图像的辐射源，用于将血管与异常组织分离的计算机单元 并且用于分割异常组织，以及用于显示分段的异常组织的输出装置。 此外，提供了一种计算机程序，用于通过辐射源来控制用于识别肺中的异常组织的计算机断层摄影机，其被设计成通过X射线辐射记录肺和血管的切片图像，以区分 来自异常组织的血管，分割异常组织并控制用于显示异常组织的输出装置。
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公开(公告)号：US20230144823A1
公开(公告)日：2023-05-11
申请号：US17917573
申请日：2021-04-06
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： RAFAEL WIEMKER , LIRAN GOSHEN , JÖRG SABCZYNSKI , TOBIAS KLINDER
CPC classification number: G06T11/008 , G06T5/50 , G06V10/751 , G06T2207/10024 , G06T2207/10081 , G06T2207/20081 , G06T2207/20221
Abstract: The invention refers to an apparatus (110) for generating an augmented image comprising a) a base image providing unit (111), wherein the base image is generated based on a combination of spectral image data, b) a contrast image providing unit (112), wherein the contrast image is generated based on a different combination of the spectral image data, c) a degree of saliency determination unit (113), 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 (114) 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.
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公开(公告)号：US20210338185A1
公开(公告)日：2021-11-04
申请号：US17285968
申请日：2019-10-18
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： AXEL SAALBACH , TOM BROSCH , TIM Philipp HARDER , HRISHIKESH NARAYANRAO DESHPANDE , EVAN SCHWAB , IVO MATTEO BALTRUSCHAT , RAFAEL WIEMKER
Abstract: This application proposes an improved medical imaging device enabling a timely communication of critical findings. The medical imaging device comprises an image acquisition unit, adapted to acquire image data of a subject to be imaged. The medical imaging device further comprises a local data processing device having an artificial-intelligence-module, Al-module, adapted to automatically detect a finding on basis of the acquired image data and to determine a priority status of the detected finding. Further, the medical imaging device comprises a notification module, adapted to provide, if the determined priority status reaches or exceeds a notification threshold, a notification data containing the detected finding. The application further proposes a medical imaging system, a method of operating a medical imaging device, a computer program element and a computer-readable medium having stored the computer program element.
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Patent Agency Ranking
公开(公告)号：US20160104280A1
公开(公告)日：2016-04-14
申请号：US14893679
申请日：2014-06-20
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： THOMAS BUELOW , MARTIN BERGTHOLDT , RAFAEL WIEMKER , KIRSTEN REGINA MEETZ , JOERG SABCZYNSKI , DOMINIK BERJAMIN KUTRA
CPC classification number: G06T7/0012 , G06T7/33 , G06T7/344 , G06T7/60 , G06T2207/10088 , G06T2207/10116 , G06T2207/10132 , G06T2207/30068 , G06T2207/30096
Abstract: The present invention provides for means for linking breast lesion locations across imaging studies. In particular, a generic three-dimensional representation of the female breast is used. Automatic translation of the lesion location into standard clinical terminology and aligning the breast model with individual patient images is comprised. Moreover, a mechanism for linking image locations showing a lesion to a location in the breast model is presented. If desired, a region of interest can be calculated by a region of interest definition module that predicts a region of interest of a known lesion in terms of the breast model representation in a new imaging study.
Abstract translation: 本发明提供了用于在成像研究之间连接乳房病变位置的手段。 特别地，使用女性乳房的通用三维表示。 将病变位置自动翻译成标准临床术语，并将乳房模型与个体患者图像对齐。 此外，呈现了将显示病变的图像位置与乳房模型中的位置相链接的机制。 如果需要，可以通过感兴趣区域模块来计算感兴趣区域，该区域在新的成像研究中根据乳房模型表示来预测已知病变的感兴趣区域。
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公开(公告)号：US20160038112A1
公开(公告)日：2016-02-11
申请号：US14774205
申请日：2014-03-14
Applicant: PHILIPS GMBH , KONINKLIJKE PHILIPS N.V.
Inventor： RAFAEL WIEMKER , THOMAS BUELOW , ANDRE GOOSSEN , KLAUS ERHARD , MARTIN BERGTHOLDT , HARALD SEPP HEESE
CPC classification number: A61B6/482 , A61B6/463 , A61B6/467 , A61B6/502 , A61B6/5235 , A61B6/54 , G06T5/50 , G06T7/0012 , G06T7/136 , G06T11/60 , G06T2207/10116 , G06T2207/20104 , G06T2207/30068 , G06T2210/41 , G06T2211/408
Abstract: A digital image (40) comprises pixels with intensities relating to different energy levels. A method for processing the digital image (40) comprises the steps of: receiving first image data (42a) and second image data (42b) of the digital image (40), the first image data (42a) encoding a first energy level and the second image data (42b) encoding a second energy level; determining a regression model (44) from the first image data (42a) and the second image data (42b), the regression model (44) establishing a correlation between intensities of pixels of the first image data (42a) with intensities of pixels of the second image data (42b); and calculating residual mode image data (46) from the first image data (42a) and the second image data (42b), such that a pixel of the residual mode image data (46) has an intensity based on the difference of an intensity of the second image data (42b) at the pixel and a correlated intensity of the pixel of the first image data (42a), the correlated intensity determinate by applying the regression model to the intensity of pixel of the first image data (42a).
Abstract translation: 数字图像（40）包括具有与不同能级相关的强度的像素。 一种处理数字图像（40）的方法包括以下步骤：接收数字图像（40）的第一图像数据（42a）和第二图像数据（42b），编码第一能级的第一图像数据（42a）和 编码第二能级的第二图像数据（42b） 从所述第一图像数据（42a）和所述第二图像数据（42b）确定回归模型（44），所述回归模型（44）建立所述第一图像数据（42a）的像素的强度与所述第一图像数据 第二图像数据（42b）; 以及从所述第一图像数据（42a）和所述第二图像数据（42b）计算残差模式图像数据（46），使得所述残留模式图像数据（46）的像素的强度基于所述第一图像数据 所述像素处的第二图像数据（42b）和所述第一图像数据（42a）的像素的相关强度，所述相关强度通过将所述回归模型应用于所述第一图像数据（42a）的像素的强度来确定。
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公开(公告)号：US20240412357A1
公开(公告)日：2024-12-12
申请号：US18702143
申请日：2022-10-12
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： RAFAEL WIEMKER , JÖRG SABCZYNSKI , CORNELIS PETRUS HENDRIKS
Abstract: A system and method for quantifying a pulmonary ventilation and perfusion gradient of a lung of a subject. Local Hounsfield density histograms are generated from computed tomography imaging data and each local histogram is cross-correlated with a global Hounsfield density histogram at a plurality of different shift values. A final shift value is determined for each local histogram based on the correlation values obtained by the cross-correlation.
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公开(公告)号：US20210181287A1
公开(公告)日：2021-06-17
申请号：US16759778
申请日：2018-10-22
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： KARSTEN SOMMER , TOM BROSCH , TIM PHILIPP HARDER , JOCHEN KEUPP , INGMAR GRAESSLIN , RAFAEL WIEMKER , AXEL SAALBACH
Abstract: The invention relates to a magnetic resonance imaging data processing system (126) for processing motion artifacts in magnetic resonance imaging data sets using a deep learning network (146, 502, 702) trained for the processing of motion artifacts in magnetic resonance imaging data sets. The magnetic resonance imaging data processing system (126) comprises a memory (134, 136) storing machine executable instructions (161, 164) and the trained deep learning network (146, 502, 702). Furthermore, the magnetic resonance imaging data processing system (126) comprises a processor (130) for controlling the magnetic resonance imaging data processing system. Execution of the machine executable instructions (161, 164) causes the processor (130) to control the magnetic resonance imaging data processing system (126) to: receive a magnetic resonance imaging data set (144, 500, 800), apply the received magnetic resonance imaging data set (144, 500, 800) as an input to the trained deep learning network (146, 502, 702), process one or more motion artifacts present in the received magnetic resonance imaging data set (144, 500, 800) using the trained deep learning network (146, 502, 702).
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公开(公告)号：US20210035291A1
公开(公告)日：2021-02-04
申请号：US16967446
申请日：2019-02-01
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： RAFAEL WIEMKER , JÖRG SABCZYNSKI , TOBIAS KLINDER
Abstract: The present invention relates to a method (200) for iterative material decomposition of multispectral image data. It is described to: a) provide (210) a plurality of spectral images of a region of interest comprising a body part; b) provide (220) a plurality of sets of material coefficients for a plurality of materials, wherein for a set of material coefficients each material coefficient is associated with a corresponding material, and wherein each set of material coefficients is associated with a corresponding spectral image of the plurality of spectral images; c) decompose (230) each spectral image of the plurality of spectral images into a plurality of material images and an offset image, wherein different material images correspond to different materials of the plurality of materials, and wherein a material image is represented by the material coefficient for the corresponding material multiplied by material concentrations at different image locations, and wherein the material coefficient is one of the material coefficients from the set of material coefficient for the corresponding spectral image; e) manipulate (240) at least one of the material images for each spectral image on the basis of at least one topological constraint relating to the body part to determine for each spectral image an updated plurality of material images and an offset image; f) recompose (250) a plurality of spectral images, wherein each recomposed spectral image is recomposed from the corresponding updated plurality of material images and the offset image; g) compare (260) intensities at image locations in a recomposed spectral image to the intensities at the image locations in its corresponding spectral image prior to recomposition to determine a plurality of corrections, wherein a correction is associated with an image location; i) modify (270) the updated plurality of material images for each spectral image comprising utilization of the corresponding plurality of corrections; j) iterate (280) steps e) to i) until convergence; and k) output (290) at least one of the recomposed spectral images at convergence and/or output at least one of the updated material images at convergence.
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