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公开(公告)号：US11386553B2
公开(公告)日：2022-07-12
申请号：US16598382
申请日：2019-10-10
发明人： Jin-hyeong Park , Sasa Grbic , Matthias Fenchel , Esther Raithel , Dana Lin
摘要： Medical image data is received at a data processing system, which is an artificial intelligence-based system. An identification process is performed at the data processing system to identify a subset of the medical image data representing a region of interest including one or more target tendons. A determination process is performed at the data processing system to determine one or more characteristics relating to one or more abnormalities of the one or more target tendons. Abnormality data is output, the abnormality data relating to the one or more abnormalities and being based on the one or more characteristics.
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公开(公告)号：US20220392614A1
公开(公告)日：2022-12-08
申请号：US17662475
申请日：2022-05-09
发明人： Michael Schwier , Bernhard Geiger , Sasa Grbic , Esther Raithel , Dana Lin , Guillaume Chabin
摘要： Techniques of determining a quantification of at least one characteristic of a muscle structure comprising at least one muscle and at least one tendon are disclosed. The quantification of the at least one characteristic of the rotator cuff may be determined by using at least one artificial neural network and based on one or more medical images depicting the muscle structure of a patient.
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公开(公告)号：US20200167911A1
公开(公告)日：2020-05-28
申请号：US16598382
申请日：2019-10-10
发明人： Jin-hyeong Park , Sasa Grbic , Matthias Fenchel , Esther Raithel , Dana Lin
摘要： Medical image data is received at a data processing system, which is an artificial intelligence-based system. An identification process is performed at the data processing system to identify a subset of the medical image data representing a region of interest including one or more target tendons. A determination process is performed at the data processing system to determine one or more characteristics relating to one or more abnormalities of the one or more target tendons. Abnormality data is output, the abnormality data relating to the one or more abnormalities and being based on the one or more characteristics.
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公开(公告)号：US20220249014A1
公开(公告)日：2022-08-11
申请号：US17168213
申请日：2021-02-05
发明人： Bernhard Geiger , Michael Schwier , Sasa Grbic , Esther Raithel , Dana Lin , Guillaume Chabin
摘要： Systems and methods for an intuitive display of one or more anatomical objects are provided. One or more 3D medical images of one or more anatomical objects of a patient are received. Correspondences between the one or more 3D medical images and points on a 2D map representing the one or more anatomical objects are determined. The 2D map is updated with patient information extracted from the one or more 3D medical images. The updated 2D map with the determined correspondences is output.
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公开(公告)号：US11630995B2
公开(公告)日：2023-04-18
申请号：US16012151
申请日：2018-06-19
发明人： Philipp Hoelzer , Sasa Grbic , Daguang Xu
IPC分类号： G06F18/2411 , G06N3/08 , G16H50/20 , G16H30/40 , G06N3/02 , G16H50/00 , G16H50/70 , G06V10/70 , G06F18/22 , G06F18/2415 , G06V10/772 , G06V10/778 , G06V10/94
摘要： The user is to be informed of the reliability of the machine-learned model based on the current input relative to the training data used to train the model or the model itself. In a medical situation, the data for a current patient is compared to the training data used to train a prediction model and/or to a decision function of the prediction model. The comparison indicates the training content relative to the current patient, so provides a user with information on the reliability of the prediction for the current situation. The indication deals with the variation of the data of the current patient from the training data or relative to the prediction model, allowing the user to see how well trained the predication model is relative to the current patient. This indication is in addition to any global confidence output through application of the prediction model to the data of the current patient.
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6.发明申请公开(公告)号：US20220092786A1
公开(公告)日：2022-03-24
申请号：US17446732
申请日：2021-09-02
发明人： Zhoubing Xu , Sasa Grbic , Dominik Neumann , Guillaume Chabin , Bruce Spottiswoode , Fei Gao , Günther Platsch
摘要： The invention describes a method for automatically localizing organ segments in a three-dimensional image comprising the following steps: providing a three-dimensional image showing at least one organ and at least one tubular network comprising a plurality of tubular structures, the organ comprising organ segments; performing automatic separation of the organ from other parts of the image; performing automatic tracing of the tubular network to obtain a branch map; performing automatic analysis of the branch map to identify specific tubular structures; performing automatically assigning regions of the organ to the specific tubular structures to segment the organ into localized organ segments; and outputting the localized organ segments and the traced and analyzed tubular network as image data. The invention further describes a localization arrangement and a medical imaging system.
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公开(公告)号：US20210342638A1
公开(公告)日：2021-11-04
申请号：US15929427
申请日：2020-05-01
摘要： Systems and methods for generating synthesized medical images for training a machine learning based network are provided. An input medical image in a first modality is received. The input medical image comprises a nodule region for each of one or more nodules and a remaining region. The input medical image comprises an annotation for each of the one or more nodules. A synthesized medical image in a second modality is generated from the input medical image. The synthesized medical image comprises the annotation for each of the one or more nodules. A synthesized nodule image of each of the nodule regions and synthesized remaining image of the remaining region are generated in the second modality. It is determined whether each particular nodule of the one or more nodules is visible in the synthesized medical image based on at least one of the synthesized nodule image for the particular nodule and the synthesized remaining image. In response to determining that at least one nodule of the one or more nodules is not visible in the synthesized medical image, the annotation for the at least one not visible nodule is removed from the synthesized nodule image.
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公开(公告)号：US20200258227A1
公开(公告)日：2020-08-13
申请号：US16861353
申请日：2020-04-29
发明人： Rui Liao , Shun Miao , Pierre de Tournemire , Julian Krebs , Li Zhang , Bogdan Georgescu , Sasa Grbic , Florin Cristian Ghesu , Vivek Kumar Singh , Daguang Xu , Tommaso Mansi , Ali Kamen , Dorin Comaniciu
摘要： Methods and systems for image registration using an intelligent artificial agent are disclosed. In an intelligent artificial agent based registration method, a current state observation of an artificial agent is determined based on the medical images to be registered and current transformation parameters. Action-values are calculated for a plurality of actions available to the artificial agent based on the current state observation using a machine learning based model, such as a trained deep neural network (DNN). The actions correspond to predetermined adjustments of the transformation parameters. An action having a highest action-value is selected from the plurality of actions and the transformation parameters are adjusted by the predetermined adjustment corresponding to the selected action. The determining, calculating, and selecting steps are repeated for a plurality of iterations, and the medical images are registered using final transformation parameters resulting from the plurality of iterations.
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公开(公告)号：US10710354B2
公开(公告)日：2020-07-14
申请号：US15729982
申请日：2017-10-11
发明人： Sasa Grbic , Dorin Comaniciu
IPC分类号： B33Y50/00 , G06T17/10 , H04N7/18 , G06T11/00 , G06T7/00 , G06T7/60 , G06F3/12 , B33Y10/00 , G05B19/4099 , B33Y30/00 , G06T7/70 , B29L31/00
摘要： A method for generating a personalized scaffold for an individual includes acquiring images of an anatomy of interest corresponding to an intended scaffold location and acquiring test results related to the anatomy of interest. One or more functional specifications are generated based on the images and test results and one or more scaffold parameters are selected based on the functional specifications. A final scaffold may then be generated using the one or more scaffold parameters.
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公开(公告)号：US20190259493A1
公开(公告)日：2019-08-22
申请号：US16272169
申请日：2019-02-11
发明人： Zhoubing Xu , Yuankai Huo , Jin-hyeong Park , Sasa Grbic , Shaohua Kevin Zhou
摘要： Medical image data may be applied to a machine-learned network learned on training image data and associated image segmentations, landmarks, and view classifications to classify a view of the medical image data, detect a location of one or more landmarks in the medical image data, and segment a region in the medical image data based on the application of the medical image data to the machine-learned network. The classified view, the segmented region, or the location of the one or more landmarks may be output.
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