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    CORRECTING SEGMENTATION OF MEDICAL IMAGES USING A STATISTICAL ANALYSIS OF HISTORIC CORRECTIONS
    11.
    发明申请
    CORRECTING SEGMENTATION OF MEDICAL IMAGES USING A STATISTICAL ANALYSIS OF HISTORIC CORRECTIONS 有权

    公开(公告)号：US20220122266A1

    公开(公告)日：2022-04-21

    申请号：US17281493

    申请日：2019-12-20

    Applicant: Brainlab AG

    Inventor： Stefan Vilsmeier ,  Andreas Blumhofer ,  Jens Schmaler

    IPC: G06T7/143 ,  G06T7/00 ,  G06T7/174

    Abstract: Disclosed is a computer-implemented methods of determining distributions of corrections for correcting the segmentation of medical image data, determining corrections for correcting the segmentation of medical image data, training a learning algorithm for determining a segmentation of a digital medical image, and determining a relation between an image representation of the anatomical body part in an individual medical image and a label to be associated with the image representation of the anatomical body part in the individual medical image using the trained machine learning algorithm. The methods encompass reading a plurality of corrections to image segmentations, wherein the corrections themselves may have been manually generated, transforming these corrections into a reference system which is not patient-specific such as an atlas reference system, conducting a statistical analysis of the correction, and applying the re-transformed result of the statistical analysis to patient images. The result of the statistical analysis may also be used to appropriately train a machine learning algorithm for automatic segmentation of patient images. The application of such a trained machine learning algorithm is also part of this disclosure.

    USING A CURRENT WORKFLOW STEP FOR CONTROL OF MEDICAL DATA PROCESSING
    12.
    发明申请
    USING A CURRENT WORKFLOW STEP FOR CONTROL OF MEDICAL DATA PROCESSING 有权

    公开(公告)号：US20220110693A1

    公开(公告)日：2022-04-14

    申请号：US17281478

    申请日：2019-12-18

    Applicant: Brainlab AG

    Inventor： Stefan Vilsmeier ,  Andreas Blumhofer ,  Jens Schmaler ,  Patrick Hiepe

    IPC: A61B34/20 ,  A61B34/10 ,  G16H50/50 ,  G16H30/40

    Abstract: Disclosed is a computer-implemented of adapting a biomechanical model of an anatomical body part of a patient to a current status of the patient. The method encompasses determination of a currently executed step of a workflow such as a medical intervention, the result of the determination serving as a basis for adapting and/or updating a biomechanical model of an anatomical body part to the corresponding current status of the patient. The determination of the current workflow step may also be used as basis for controlling an imaging device for tracking entities around the patient or for imaging the anatomical body part or acquiring further data or for urging the user to perform a specific action such as acquisition of information using a tracked instrument such as a pointer. The biomechanical model has been generated from atlas data. The data sets which are generated according to the current workflow step may additionally or alternatively serve as a basis for determining the current workflow step and/or adapting the further workflow.

    Matching patient images and images of an anatomical atlas
    14.
    发明授权
    Matching patient images and images of an anatomical atlas 有权

    公开(公告)号：US10262418B2

    公开(公告)日：2019-04-16

    申请号：US15608199

    申请日：2017-05-30

    Applicant: Brainlab AG

    Inventor： Andreas Blumhofer

    IPC: G06K9/00 ,  G06T7/00 ,  G06T3/00 ,  G06T11/00 ,  G06T7/30 ,  G06T7/32 ,  G06T7/38 ,  G06F19/00 ,  G16H50/50

    Abstract: A matching transformation is determined for matching a patient image set of images of an anatomical body structure of a patient with an atlas image set of images of a general anatomical structure including anatomical atlas elements. Atlas spatial information containing spatial information on the general anatomical structure, and element representation information are obtained. The element representation information describes representation data sets which contain information on representations of the plurality of atlas elements in the atlas images to be determined are obtained, and also describes a determination rule for determining respective representation data sets for respective atlas elements in accordance with different respective parameter sets. Patient data is acquired by acquiring the patient image set and the parameter sets which are respectively associated with the images of the patient image set. The matching transformation is determined by matching images associated with the same parameter set to each other.

    Matching Patient Images of Different Imaging Modality Using Atlas Information
    17.
    发明申请
    Matching Patient Images of Different Imaging Modality Using Atlas Information 有权
    使用Atlas信息匹配不同成像模式的患者图像

    公开(公告)号：US20150294467A1

    公开(公告)日：2015-10-15

    申请号：US14437784

    申请日：2013-06-28

    Applicant: BRAINLAB AG

    Inventor： Andreas Blumhofer ,  Bálint Varkuti ,  Jens Schmaler

    IPC: G06T7/00 ,  G06T11/00

    CPC classification number: G06T7/0012 ,  G06F19/00 ,  G06F19/321 ,  G06T3/0056 ,  G06T7/30 ,  G06T7/32 ,  G06T7/38 ,  G06T11/008 ,  G06T2207/10004 ,  G06T2207/10076 ,  G06T2207/10081 ,  G06T2207/10084 ,  G06T2207/10088 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20104 ,  G06T2207/20128 ,  G06T2207/20221 ,  G06T2207/30004 ,  G06T2207/30196 ,  G16H50/50

    Abstract: The present invention relates to a medical data processing method of transforming a representation of an anatomical structure (1) of a patient in a first imaging modality into a representation of the anatomical structure (1′) in a second, other imaging modality, the method being constituted to be executed by a computer and comprising the following steps: a) acquiring (S1) first modality image data describing the first modality medical image containing the representation of the anatomical structure (1) in the first imaging modality; b) acquiring (S1) atlas data describing a first modality atlas image describing a general structure of the anatomical structure (1) in the first imaging modality, the atlas data containing information about the representation of the general structure in the second imaging modality; c) determining (S3), based on the first modality image data and the atlas data, a first matching transformation between the first modality medical image and the first modality atlas image; d) determining (S5), based on the first matching transformation and the first modality atlas image and the information about the representation of the general structure in the second imaging modality second modality, a second modality image representation of the first modality medical

    Abstract translation: 本发明涉及将第一成像模式中的患者的解剖结构（1）的表示变换为第二其他成像模态中的解剖结构（1'）的表示的医疗数据处理方法，该方法 被构造为由计算机执行并且包括以下步骤：a）获取（S1）描述在第一成像模式中包含解剖结构（1）的表示的第一模态医学图像的第一模态图像数据; b）获取（S1）描述描述第一成像模态中解剖结构（1）的一般结构的第一模态图集的图像数据，所述图集数据包含关于第二成像模态中的一般结构的表示的信息; c）基于第一模态图像数据和图集数据确定（S3）第一模态医学图像和第一模态图谱之间的第一匹配变换; d）基于第一匹配变换和第一模态图集和关于第二成像模态第二模态中的一般结构的表示的信息来确定（S5），第一模态医学的第二模态图像表示

    LOCALIZATION OF FIBROUS NEURAL STRUCTURES
    18.
    发明申请
    LOCALIZATION OF FIBROUS NEURAL STRUCTURES 审中-公开
    纤维神经结构局部化

    公开(公告)号：US20150164366A1

    公开(公告)日：2015-06-18

    申请号：US14419961

    申请日：2012-08-09

    Applicant: Brainlab AG

    Inventor： Rainer Lachner ,  Andreas Blumhofer

    IPC: A61B5/055 ,  G06F19/00 ,  A61B5/00

    CPC classification number: A61B5/055 ,  A61B5/4893 ,  A61B5/7275 ,  G06F19/34 ,  G06T7/11 ,  G06T2207/10092 ,  G06T2207/20128 ,  G06T2207/30016

    Abstract: A data processing method for determining a path of a neural fibre in a patient, comprising the steps of: a) acquiring an atlas dataset representing an atlas of a fibrous structure comprising the neural fibre b) acquiring a nerve indicating dataset comprising information suitable for identifying the neural fibre in the patient c) calculating a matched atlas dataset by registering the atlas dataset with the nerve indicating dataset d) obtaining a generic path of the neural fibre from the matched atlas dataset e) defining a constraining volume in the patient around the generic path, the constraining volume having at least two end surfaces on which the generic path ends and f) determining the path of the neural fibre between end surfaces using a probabilistic approach, wherein the determined path lies completely within the constraining volume.

    Abstract translation: 一种用于确定患者中的神经纤维的路径的数据处理方法，包括以下步骤：a）获取表示包含所述神经纤维的纤维结构的图集的图谱数据集b）获取神经指示数据集，其包含适于识别的信息 患者中的神经纤维c）通过将图谱数据集与神经指示数据集注册来计算匹配的图集数据集d）从匹配的图集数据集获得神经纤维的通用路径e）在通用的定义周围的患者中定义约束体积 所述约束体积具有至少两个端面，所述通用路径终止于所述至少两个端面，以及f）使用概率方法确定所述神经纤维在端面之间的路径，其中所确定的路径完全位于约束体积内。

    Constrained object correction for a segmented image
    19.
    发明授权
    Constrained object correction for a segmented image 有权

    公开(公告)号：US12190522B2

    公开(公告)日：2025-01-07

    申请号：US18306656

    申请日：2023-04-25

    Applicant: Brainlab AG

    Inventor： Jens Schmaler ,  Andreas Giese ,  Andreas Blumhofer

    IPC: G06T7/70 ,  G06T7/00 ,  G06T7/11 ,  G06T7/20

    Abstract: Disclosed is a computer-implemented method of segmenting a medical patient image using an atlas and relating the segmentation result to a model of possible geometric changes to the segmentation result (e.g. for correcting the position of the segmentation of anatomical structures) which consider for example anatomical limitations. The thus-related segmentation result may be used as a basis for changing and/or correcting the position, shape and/or orientation of at least parts of the segmentation result, e.g. by user interaction. The invention also relates to an atlas data set comprising information such as values of the variables of the model of possible geometric changes in relation to the positions of anatomical structures in the atlas.

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