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    DEEP LEARNING BASED PROCESSING OF MOTION ARTIFACTS IN MAGNETIC RESONANCE IMAGING DATA
    11.
    发明申请
    DEEP LEARNING BASED PROCESSING OF MOTION ARTIFACTS IN MAGNETIC RESONANCE IMAGING DATA 有权

    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

    IPC: G01R33/565 ,  G01R33/56 ,  G06T5/00 ,  G06T7/00 ,  G06T5/50 ,  G06T5/20 ,  G06N3/08 ,  G06N3/04

    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).

    APPARATUS FOR IDENTIFYING OBJECTS FROM AN OBJECT CLASS
    12.
    发明申请
    APPARATUS FOR IDENTIFYING OBJECTS FROM AN OBJECT CLASS 审中-公开

    公开(公告)号：US20190354816A1

    公开(公告)日：2019-11-21

    申请号：US16463390

    申请日：2017-12-01

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： RAFAEL WIEMKER ,  TOBIAS KLINDER ,  AXEL SAALBACH ,  JENS VON BERG

    IPC: G06K9/62 ,  G06K9/48 ,  G06T7/60 ,  G06T7/00 ,  G06T7/13

    Abstract: The invention relates to an apparatus for identifying a candidate object in image data and determining a likelihood that the candidate object is an object from an object class. The apparatus comprises an image data receiving unit for receiving image data of an object of the object class, a seed element selecting unit for selecting a portion of the image elements as seed elements, a contour point identifying unit for identifying, for each seed element (SE), contour points, the contour points of a seed element circumscribing a candidate object which comprises the seed element, and a seed score determining unit for determining, for each seed element, a seed score indicative of a likelihood that the candidate object is an object from the object class. The invention allows differentiation between an object of an object class of interest and artifacts.

    MODEL-BASED SEGMENTATION OF AN ANATOMICAL STRUCTURE
    13.
    发明申请
    MODEL-BASED SEGMENTATION OF AN ANATOMICAL STRUCTURE 有权
    基于模型的分解结构分解

    公开(公告)号：US20160307331A1

    公开(公告)日：2016-10-20

    申请号：US15101018

    申请日：2014-12-15

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： SABINE MOLLUS ,  AXEL SAALBACH ,  JUERGEN WEESE

    IPC: G06T7/00

    CPC classification number: G06T7/149 ,  G06F19/321 ,  G06T7/344 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20124 ,  G06T2207/20132 ,  G06T2207/30048 ,  G06T2210/41 ,  G16H30/40

    Abstract: A system and method is provided which obtains different medical images (210) showing an anatomical structure of a patient and having been acquired by different medical imaging modalities and/or different medical imaging protocols. The system is configured for fitting a first deformable model to the anatomical structure in the first medical image (220A), fitting a second deformable model to the anatomical structure in the second medical image (220B), mutually aligning the first fitted model and the second fitted model (230), and subsequently fusing the first fitted model and the second fitted model to obtain a fused model (240) by augmenting the first fitted model with a part of the second fitted model which is missing in the first fitted model; or adjusting or replacing a part of the first fitted model based on a corresponding part of the second fitted model having obtained a better fit. The fused model represents a multimodal/multi-protocol segmentation of the anatomical structure, and provides a user with a more comprehensive understanding of the anatomical structure than known models.

    Abstract translation: 提供一种系统和方法，其获得示出患者的解剖结构并且已经通过不同的医学成像模式和/或不同的医学成像协议获取的不同的医学图像（210）。 该系统被配置为将第一可变形模型拟合到第一医学图像（220A）中的解剖结构，将第二可变形模型拟合到第二医学图像（220B）中的解剖结构，使第一拟合模型和第二医学图像 以及随后使所述第一拟合模型和所述第二拟合模型融合，以通过在所述第一拟合模型中缺少所述第二拟合模型的一部分来增加所述第一拟合模型来获得融合模型（240） 或者基于获得更好拟合的第二拟合模型的对应部分来调整或替换第一拟合模型的一部分。 融合模型表示解剖结构的多模式/多协议分割，并为用户提供对已知模型的解剖结构的更全面了解。

    BASELINE IMAGE GENERATION FOR DIAGNOSTIC APPLICATIONS
    14.
    发明申请
    BASELINE IMAGE GENERATION FOR DIAGNOSTIC APPLICATIONS 有权

    公开(公告)号：US20250046428A1

    公开(公告)日：2025-02-06

    申请号：US18717494

    申请日：2022-12-06

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： AXEL SAALBACH ,  TIM PHILIPP HARDER ,  THOMAS BUELOW ,  ANDRE GOOSSEN ,  SVEN KROENKE-HILLE ,  JENS VON BERG ,  MICHAEL GRASS

    IPC: G16H30/40 ,  G06F3/04842 ,  G06T5/77 ,  G06V10/82 ,  G16H30/20 ,  G16H50/20 ,  G16H50/70

    Abstract: Technology provides baseline images for diagnostic applications, including receiving a diagnostic image relating to a condition of a patient, the diagnostic image reflecting one of a normal state or an abnormal state of the condition, and generating a baseline image via a neural network using the diagnostic image, where the neural network is trained to generate a prediction of the diagnostic image reflecting a normal state of the condition. The neural network can include a generative adversarial network (GAN) trained only on image data with a normal state of the condition, where generating the baseline image includes an optimization process to maximize a similarity between the diagnostic image and a response of the GAN. Generating the baseline image can include selecting a portion of the diagnostic image, and adjusting a relevance weighting to be applied to the selected portion of the diagnostic image in the optimization process.

    MODEL-BASED SEGMENTATION OF AN ANATOMICAL STRUCTURE
    18.
    发明申请
    MODEL-BASED SEGMENTATION OF AN ANATOMICAL STRUCTURE 有权

    公开(公告)号：US20170213338A1

    公开(公告)日：2017-07-27

    申请号：US15038834

    申请日：2014-11-26

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： ALEXANDRA GROTH ,  JOCHEN PETERS ,  JUERGEN WEESE ,  AXEL SAALBACH

    IPC: G06T7/00 ,  G06T7/12

    CPC classification number: G06T7/0012 ,  G06T7/12 ,  G06T7/149 ,  G06T2207/30048

    Abstract: A system (100) is provided for performing a model-based segmentation of an anatomical structure in a medical image. The system comprises a processor (140) configured for performing a model-based segmentation of the anatomical structure by applying a deformable model to image data (042). Moreover, definition data (220) is provided which defines a geometric relation between a first part and a second part of the deformable model of which a corresponding first part of the anatomical structure is presumed to be better visible in the image data than a corresponding second part of the anatomical structure. The definition data is then used to adjust a fit of the second part of the deformable model. As a result, a better fit of the second part of the deformable model to the second part of the anatomical structure is obtained despite said part being relatively poorly visible in the image data.

    APPARATUS FOR MEDICAL IMAGE ANALYSIS
    19.
    发明公开
    APPARATUS FOR MEDICAL IMAGE ANALYSIS 审中-公开

    公开(公告)号：US20240257345A1

    公开(公告)日：2024-08-01

    申请号：US18564246

    申请日：2022-05-12

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： MICHAEL GRASS ,  IVO MATTEO BALTRUSCHAT ,  AXEL SAALBACH

    IPC: G06T7/00 ,  G16H30/40

    CPC classification number: G06T7/0012 ,  G16H30/40 ,  G06T2207/10088 ,  G06T2207/10116 ,  G06T2207/30004 ,  G06T2207/30168

    Abstract: The present invention relates to an apparatus (10) for medical image analysis, comprising: a camera (20); a processing unit (30); and an output unit (40). The camera is configured to be placed in proximity of a system image display of a medical imaging system. The camera is configured to acquire a local image of a system image displayed on the system image display, wherein the system image comprises medical image data of a patient and wherein the local image comprises local image data of the medical image data of the patient. The processing unit is configured to determine a plurality of image and imaging parameters, the determination comprising utilization of the local image. The processing unit is configured utilize the plurality of image and imaging parameters to determine a process decision to: either determine if the local image data of the medical image data is suitable for further processing; or determine if a new local image is to be acquired and a new plurality of image and imaging parameters determined for the new local image and the new plurality of image and imaging parameters utilized to determine a new process decision. The output unit is configured to output image data.

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