MEDICAL IMAGING AND ANALYSIS METHOD

    公开(公告)号:US20240404055A1

    公开(公告)日:2024-12-05

    申请号:US18695880

    申请日:2022-09-29

    Abstract: A method is provided for analyzing survey imaging data. The method comprises acquiring first image data with a first imaging protocol covering a first FOV, processing the data with an anatomical analysis program or routine to detect at least a portion of a target anatomy, and performing a coverage check adapted to determine whether the target anatomy is fully covered within the first FOV. Second image data is subsequently acquired in accordance with a second imaging protocol defining a second FOV. The second imaging protocol may be: the same as the first, but wherein the results of the coverage check are stored and linked with the second image data for later use; different to the first and wherein the results of the coverage check are output to a user interface and a user input responsive thereto is used to determine the second scan protocol; or different to the first, but wherein an adjusted second scan protocol is automatically determined.

    RADIOLOGY QUALITY DASHBOARD DATA ANALYSIS AND INSIGHT ENGINE

    公开(公告)号:US20230113060A1

    公开(公告)日:2023-04-13

    申请号:US17913252

    申请日:2021-03-16

    Abstract: A non-transitory computer readable medium (26) stores instructions readable and executable by at least one electronic processor (20) to provide statistical analysis on one or more radiology databases (30, 32) in conjunction with a workstation (18) having a display device (24) and at least one user input device (22). The instructions include: instructions readable and executable by the at least one electronic processor to provide a plurality of different analysis services (39) for selecting and processing exam data stored in the one or more radiology databases; and user guidance instructions readable and executable by the at least one electronic processor to guide a user in creating and executing a workflow (38) by providing a graphical user interface (GUI) (28) on the workstation having menus nd/or GUI dialogs (40) for user selection, configuration, and execution of an ordered sequence of analysis services and providing data persistence between the analysis services of the ordered sequence of analysis services.

    VISUALIZING VOLUMETRIC IMAGE OF ANATOMICAL STRUCTURE

    公开(公告)号:US20180025546A1

    公开(公告)日:2018-01-25

    申请号:US15513184

    申请日:2015-09-18

    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.

    IDENTIFYING ABNORMAL TISSUE IN IMAGES OF COMPUTED TOMOGRAPHY
    4.
    发明申请
    IDENTIFYING ABNORMAL TISSUE IN IMAGES OF COMPUTED TOMOGRAPHY 审中-公开
    识别计算机图像图像异常组织

    公开(公告)号:US20140330119A1

    公开(公告)日:2014-11-06

    申请号:US14334176

    申请日:2014-07-17

    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。

    METHOD FOR PROVDING FEEDBACK DATA IN A MEDICAL IMAGING SYSTEM

    公开(公告)号:US20240366177A1

    公开(公告)日:2024-11-07

    申请号:US18561312

    申请日:2022-05-09

    Abstract: A method for providing feedback data in a medical imaging system (22) for a medical imaging process, comprising the steps of: providing, by a calculation unit, a simulation model, trained to predict an appearance of a medical image to be acquired by using the medical imaging system (22) from a relation between subject positioning data associated with a captured positioning of a subject (27), equipment positioning data associated with a captured positioning of at least one medical care and/or monitoring equipment (28, 30) arranged in or at the subject (27) in a medical imaging system (22), and medical image data associated with the subject positioning data and the medical care and/or monitoring equipment positioning data (S10); obtaining, by the calculation unit, from at least one measuring means (25, 26), current subject positioning data of a subject (27) and current medical equipment positioning data of at least one medical care and/or monitoring equipment (28, 30) arranged in or at the subject (27) in the medical imaging system (S20); determining, by the calculation unit, feedback data by feeding the obtained current subject positioning data and the obtained current medical equipment positioning data into the simulation model outputting the feedback data, wherein the feedback data comprise at least simulated medical image data predicted by the simulation model from the obtained current subject positioning data and current medical equipment positioning data (S30); providing, by a provision unit, the feedback data (S40).

    LINKING BREAST LESION LOCATIONS ACROSS IMAGING STUDIES
    7.
    发明申请
    LINKING BREAST LESION LOCATIONS ACROSS IMAGING STUDIES 审中-公开
    与成像研究相关联的乳腺切除位置

    公开(公告)号:US20160104280A1

    公开(公告)日:2016-04-14

    申请号:US14893679

    申请日:2014-06-20

    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。

    DETERMINING A RESIDUAL MODE IMAGE FROM A DUAL ENERGY IMAGE
    8.
    发明申请
    DETERMINING A RESIDUAL MODE IMAGE FROM A DUAL ENERGY IMAGE 有权
    从双能量图像确定残留模式图像

    公开(公告)号:US20160038112A1

    公开(公告)日:2016-02-11

    申请号:US14774205

    申请日:2014-03-14

    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。

    BASELINE IMAGE GENERATION FOR DIAGNOSTIC APPLICATIONS

    公开(公告)号:US20250046428A1

    公开(公告)日:2025-02-06

    申请号:US18717494

    申请日:2022-12-06

    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.

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