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1. 发明授权

US10977390B2 Anonymisation of medical patient images using an atlas 有权
公开(公告)号：US10977390B2
公开(公告)日：2021-04-13
申请号：US16754419
申请日：2019-02-28
申请人： Brainlab AG
发明人： Andreas Blumhofer , Jens Schmaler
IPC分类号： G06K9/00 , G06F21/62 , G06T5/00 , G16H30/40
摘要： Disclosed is a computer-implemented method for generating an anonymized medical image of an anatomical body part of a patient, a corresponding computer program, a program storage medium storing such a program and a computer for executing the program, as well as a medical system comprising an electronic data storage device and the aforementioned computer. The disclosed method encompasses establishing a mapping from a patient image onto an atlas, changing that mapping, and applying the inverse of the changed mapping to the atlas in order to transform image content from the atlas to the patient image in order to achieve a deformed and thereby anonymised appearance of the patient image.

2. 发明授权

US11669974B2 Constrained object correction for a segmented image 有权
公开(公告)号：US11669974B2
公开(公告)日：2023-06-06
申请号：US17853307
申请日：2022-06-29
申请人： Brainlab AG
发明人： Jens Schmaler , Andreas Giese , Andreas Blumhofer
IPC分类号： G06T7/11 , G06T7/70 , G06T7/00 , G06T7/20
CPC分类号： G06T7/11 , G06T7/0012 , G06T7/20 , G06T7/70 , G06T2207/20128 , G06T2207/30081
摘要： 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.

3. 发明申请

US20220122255A1 MEDICAL IMAGE ANALYSIS USING MACHINE LEARNING AND AN ANATOMICAL VECTOR 有权
公开(公告)号：US20220122255A1
公开(公告)日：2022-04-21
申请号：US17281472
申请日：2019-12-19
申请人： Brainlab AG
发明人： Stefan Vilsmeier , Jens Schmaler
IPC分类号： G06T7/00 , G06V10/82 , G06V20/69 , G06T7/136
摘要： Disclosed is a computer-implemented method which encompasses registering a tracked imaging device such as a microscope having a known viewing direction and an atlas to a patient space so that a transformation can be established between the atlas space and the reference system for defining positions in images of an anatomical structure of the patient. Labels are associated with certain constituents of the images and are input into a learning algorithm such as a machine learning algorithm, for example a convolutional neural network, together with the medical images and an anatomical vector and for example also the atlas to train the learning algorithm for automatic segmentation of patient images generated with the tracked imaging device. The trained learning algorithm then allows for efficient segmentation and/or labelling of patient images without having to register the patient images to the atlas each time, thereby saving on computational effort.

4. 发明授权

US11877809B2 Using a current workflow step for control of medical data processing 有权
公开(公告)号：US11877809B2
公开(公告)日：2024-01-23
申请号：US17281478
申请日：2019-12-18
申请人： Brainlab AG
发明人： Stefan Vilsmeier , Andreas Blumhofer , Jens Schmaler , Patrick Hiepe
IPC分类号： A61B5/00 , A61B34/20 , A61B34/10 , G16H50/50 , G16H30/40 , G06V10/25 , G06V10/10 , G06T7/00
CPC分类号： A61B34/20 , A61B34/10 , G06T7/0012 , G06V10/17 , G06V10/25 , G16H30/40 , G16H50/50 , A61B2034/102 , A61B2034/105 , A61B2034/2063 , A61B2034/2065
摘要： 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.

5. 发明授权

US11593519B2 Anonymisation of medical patient images using an atlas 有权
公开(公告)号：US11593519B2
公开(公告)日：2023-02-28
申请号：US17225000
申请日：2021-04-07
申请人： Brainlab AG
发明人： Andreas Blumhofer , Jens Schmaler
IPC分类号： G06K9/00 , G06F21/62 , G16H30/40 , G06T5/00
摘要： Disclosed is a computer-implemented method for generating an anonymized medical image of an anatomical body part of a patient, a corresponding computer program, a program storage medium storing such a program and a computer for executing the program, as well as a medical system comprising an electronic data storage device and the aforementioned computer. The disclosed method encompasses establishing a mapping from a patient image onto an atlas, changing that mapping, and applying the inverse of the changed mapping to the atlas in order to transform image content from the atlas to the patient image in order to achieve a deformed and thereby anonymised appearance of the patient image.

6. 发明授权

US09639938B2 Matching patient images of different imaging modality using atlas information 有权
公开(公告)号：US09639938B2
公开(公告)日：2017-05-02
申请号：US14437784
申请日：2013-06-28
申请人： Brainlab AG
发明人： Andreas Blumhofer , Bálint Varkuti , Jens Schmaler
IPC分类号： G06K9/00 , G06T7/00 , G06T3/00 , G06T11/00
CPC分类号： 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
摘要： The present invention relates to a medical data processing method of transforming a representation of an anatomical structure of a patient in a first imaging modality into a representation of the anatomical structure in a second, other imaging modality, the method being constituted to be executed by a computer and comprising the following steps: acquiring first modality image data describing the first modality medical image containing the representation of the anatomical structure in the first imaging modality; acquiring atlas data describing a first modality atlas image describing a general structure of the anatomical structure in the first imaging modality, the atlas data containing information about the representation of the general structure in the second imaging modality; determining, 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; determining, 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 image.

7. 发明申请

US20220122266A1 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
申请人： Brainlab AG
发明人： Stefan Vilsmeier , Andreas Blumhofer , Jens Schmaler
IPC分类号： G06T7/143 , G06T7/00 , G06T7/174
摘要： 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.

8. 发明申请

US20220110693A1 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
申请人： Brainlab AG
发明人： Stefan Vilsmeier , Andreas Blumhofer , Jens Schmaler , Patrick Hiepe
IPC分类号： A61B34/20 , A61B34/10 , G16H50/50 , G16H30/40
摘要： 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.

9. 发明申请

US20150294467A1 Matching Patient Images of Different Imaging Modality Using Atlas Information 有权
标题翻译：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
申请人： BRAINLAB AG
发明人： Andreas Blumhofer , Bálint Varkuti , Jens Schmaler
IPC分类号： G06T7/00 , G06T11/00
CPC分类号： 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
摘要： 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
摘要翻译：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

10. 发明公开

US20240062517A1 MEDICAL IMAGE ANALYSIS USING MACHINE LEARNING AND AN ANATOMICAL VECTOR 审中-公开
公开(公告)号：US20240062517A1
公开(公告)日：2024-02-22
申请号：US18496306
申请日：2023-10-27
申请人： Brainlab AG
发明人： Stefan Vilsmeier , Jens Schmaler
IPC分类号： G06V10/764 , G06T7/00 , G06T7/136 , G06T7/70 , G06V10/26 , G06V10/774 , G06V10/82 , G06V20/69 , G06V20/70
CPC分类号： G06V10/764 , G06T7/0014 , G06T7/136 , G06T7/70 , G06V10/26 , G06V10/774 , G06V10/82 , G06V20/695 , G06V20/698 , G06V20/70 , G06T2207/10056 , G06T2207/10061 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004 , G06V2201/03
摘要： Disclosed is a computer-implemented method which encompasses registering a tracked imaging device such as a microscope having a known viewing direction and an atlas to a patient space so that a transformation can be established between the atlas space and the reference system for defining positions in images of an anatomical structure of the patient. Labels are associated with certain constituents of the images and are input into a learning algorithm such as a machine learning algorithm, for example a convolutional neural network, together with the medical images and an anatomical vector and for example also the atlas to train the learning algorithm for automatic segmentation of patient images generated with the tracked imaging device. The trained learning algorithm then allows for efficient segmentation and/or labelling of patient images without having to register the patient images to the atlas each time, thereby saving on computational effort.

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