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公开(公告)号:US20240335177A1
公开(公告)日:2024-10-10
申请号:US18745450
申请日:2024-06-17
发明人: Sandra HADER
摘要: A computer-implemented method is for performing at least one medical imaging procedure using an imaging modality. The medical imaging procedure is performed under remote supervision. An embodiment of the method includes acquiring with a computing unit data on the medical imaging procedure to be performed; acquiring with the computing unit data on at least one expert operator, located at a workplace remote from the imaging modality; matching data on the medical imaging procedure with data on the expert operator; assigning at least one expert operator to the medical imaging procedure based on the matching; and providing a communication channel between the imaging modality and the remote workplace.
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公开(公告)号:US20240273362A1
公开(公告)日:2024-08-15
申请号:US18568454
申请日:2022-10-14
发明人: Giovanni Valbusa , Sonia Colombo Serra , Alberto Fringuello Mingo , Fabio Tedoldi , Davide Bella
CPC分类号: G06N3/08 , G06N20/00 , G06T7/0012 , G16H30/00 , G06T2207/20081 , G06T2207/20084
摘要: A solution is proposed for training a machine learning model (420) for use in medical imaging applications. A corresponding method (700) comprises providing (703-743: 759-763) sample sets, each comprising a sample baseline image, a sample target image (acquired from a corresponding body-part of a subject to which a contrast agent at a certain dose has been administered) and a sample source dose (corresponding to a different dose of the contrast agent). The machine learning model (420) is trained (744-758) so as to optimize its capability of generating each sample target image from the corresponding sample baseline image and sample source image. One or more of the sample sets are incomplete, missing their sample source images. Each incomplete sample set is completed (704-742: 759-763) by simulating the sample source image from at least the sample baseline image and the sample target image of the sample set. A computer programs (500) and a computer program products for implementing the method (700) are proposed. Moreover, a computing system (130) for performing the method (700) is proposed.
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公开(公告)号:US12062423B2
公开(公告)日:2024-08-13
申请号:US17068858
申请日:2020-10-13
发明人: Gregory J. Bakos , Jason L. Harris , Frederick E. Shelton, IV , James. Fleming , Michael Hutchinson , Francesco N. Albertini , Anthony DiUbaldi , Steven Vesole , Kevin L. Houser
CPC分类号: G16H20/17 , A61M5/315 , G16H10/60 , G16H30/00 , G16H40/67 , A61M2205/18 , A61M2205/502 , A61M2205/52
摘要: In general, drug administration devices that communicate with surgical hubs and methods of using drug administration devices that communicate with surgical hubs are provided. In one aspect, a surgical system is provided that in one embodiment includes a drug administration device configured to administer a drug to a patient during performance of a surgical procedure. The drug administration device includes a first communications interface and a first processor configured to cause the first communications interface to transmit data regarding operation of the drug administration device during the performance of the surgical procedure. The surgical system also includes a surgical hub including a second processor and a second communications interface. The second communications interface is configured to receive the transmitted data from the first communications interface during the performance of the surgical procedure.
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公开(公告)号:US20240194325A1
公开(公告)日:2024-06-13
申请号:US18586727
申请日:2024-02-26
IPC分类号: G16H30/20 , G06F16/14 , G06F40/40 , G16H10/20 , G16H10/60 , G16H30/00 , G16H30/40 , G16H40/00 , G16H80/00 , H04L67/12
CPC分类号: G16H30/20 , G06F16/14 , G06F40/40 , G16H10/20 , G16H30/00 , G16H30/40 , G16H40/00 , H04L67/12 , G06T2210/41 , G06V2201/03 , G16H10/60 , G16H80/00
摘要: A system and method for processing a plurality of medical images using a plurality of clinical applications. A current study is received by a first server, the current study having first image series metadata. The first server can determine, based on several different techniques, that the current study is in progress. The system and method generates an assembled study set comprising the current study that is processed using a clinical application, the current study having a first series and a second series.
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公开(公告)号:US12008310B2
公开(公告)日:2024-06-11
申请号:US17846355
申请日:2022-06-22
IPC分类号: G16H40/20 , A61B5/00 , G06F3/16 , G06F16/635 , G06F16/683 , G06F16/904 , G06F18/25 , G06F21/62 , G06F40/174 , G06F40/30 , G06F40/40 , G06K19/077 , G06N3/006 , G06T7/00 , G06V20/10 , G06V20/52 , G06V40/10 , G06V40/16 , G06V40/20 , G10L15/08 , G10L17/00 , G10L21/0232 , G11B27/10 , G16B50/00 , G16H10/20 , G16H10/60 , G16H15/00 , G16H30/00 , G16H30/20 , G16H30/40 , G16H40/60 , G16H40/63 , G16H50/20 , G16H50/30 , G16H80/00 , G16Y20/00 , H04L51/02 , H04L51/222 , H04N7/18 , H04R1/32 , H04R3/00 , H04R3/12 , G10L15/18 , G10L15/22 , G10L15/26 , G10L21/0208 , H04R1/40 , H04R3/02
CPC分类号: G06F40/174 , A61B5/7405 , G06F3/16 , G06F16/637 , G06F16/685 , G06F16/904 , G06F18/25 , G06F21/6245 , G06F40/30 , G06F40/40 , G06K19/07762 , G06N3/006 , G06T7/00 , G06V20/10 , G06V20/52 , G06V40/103 , G06V40/16 , G06V40/172 , G06V40/23 , G10L15/08 , G10L17/00 , G10L21/0232 , G11B27/10 , G16B50/00 , G16H10/20 , G16H10/60 , G16H15/00 , G16H30/00 , G16H30/20 , G16H30/40 , G16H40/20 , G16H40/60 , G16H40/63 , G16H50/20 , G16H50/30 , G16H80/00 , G16Y20/00 , H04L51/02 , H04L51/222 , H04N7/183 , H04R1/326 , H04R3/005 , H04R3/12 , G06T2207/10024 , G06T2207/10044 , G06T2207/10048 , G06T2207/10116 , G06T2207/10132 , G10L15/1815 , G10L15/22 , G10L15/26 , G10L2021/02082 , H04N7/181 , H04R1/406 , H04R3/02 , H04R2420/07 , H04S2400/15
摘要: A method, computer program product, and computing system for compartmentalizing a virtual assistant is executed on a computing device and includes obtaining encounter information via a compartmentalized virtual assistant during a patient encounter, wherein the compartmentalized virtual assistant includes a core functionality module. One or more additional functionalities are added to the compartmentalized virtual assistant on an as-needed basis.
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公开(公告)号:US20240177827A1
公开(公告)日:2024-05-30
申请号:US18430785
申请日:2024-02-02
申请人: PAIGE.AI, Inc.
摘要: Systems and methods are disclosed for providing automated routing of medical data, comprising determining at least one rule corresponding to at least one condition and at least one receiver, receiving medical data and associated medical metadata, determining whether the medical data, the associated medical metadata, and/or associated artificial intelligence processing satisfies the at least one condition of the at least one rule, and upon determining that the at least one condition of the at least one rule is satisfied, providing, from an originating institution, the medical data to the at least one receiver.
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公开(公告)号:US11992372B2
公开(公告)日:2024-05-28
申请号:US17062508
申请日:2020-10-02
发明人: Frederick E. Shelton, IV , Jason L. Harris , Kevin M. Fiebig , Michael J. Vendely , Shane R. Adams
IPC分类号: A61B34/35 , A61B18/14 , A61B90/00 , G06F3/048 , G09G3/00 , G09G5/30 , G16H20/40 , G16H30/00 , G16H40/60
摘要: A surgical hub may have cooperative interactions with one of more means of displaying the image from the laparoscopic scope and information from one of more other smart devices. The surgical hub may have the capacity of interacting with these multiple displays using an algorithm or control program that enables the combined display and control of the data distributed across the number of displays in communication with the surgical hub. The hub can obtain display control parameter(s) associated with a surgical procedure. The hub may determine, based on the display control parameter, different contents for different displays. The hub may generate and send the display contents to their respective displays. For example, the visualization control parameter may be a progression of the surgical procedure. The surgical hub may determine different display contents for the primary and the secondary displays based on the progression of the surgical procedure.
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公开(公告)号:US11967421B2
公开(公告)日:2024-04-23
申请号:US16981331
申请日:2019-03-06
IPC分类号: G16H40/40 , G06F11/30 , G06F40/205 , G06F40/211 , G06N5/025 , G06N5/04 , G16H30/00
CPC分类号: G16H40/40 , G06F11/30 , G06F40/205 , G06F40/211 , G06N5/025 , G06N5/04 , G16H30/00
摘要: In a monitoring method for generating maintenance alerts, component IDs are extracted which identify medical imaging device components in electronic medical imaging device manuals (25, 26, 27, 28). Operating parameters of the medical imaging device components and associated operating parameter ranges are also extracted from the manuals, based on numeric values, parameter terms identifying operating parameters, and linking terms or symbols indicative of equality or inequality that connect the numeric values and parameter terms. The operating parameter ranges are formulated into decision rules (36) which are applied to log data (40) generated by a monitored medical imaging device (2) to detect out-of-range log data generated by the monitored medical imaging device. Maintenance alerts (24) are displayed on a display (18) in response to the detected out-of-range log data. The maintenance alerts are generated from out-of-range log data and are associated with component IDs contained in the out-of-range log data.
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公开(公告)号:US11853691B2
公开(公告)日:2023-12-26
申请号:US17210052
申请日:2021-03-23
IPC分类号: G16H10/60 , A61B5/00 , G06F3/16 , G06F16/635 , G06F16/683 , G06F16/904 , G06F21/62 , G06F40/174 , G06F40/30 , G06F40/40 , G06K9/62 , G06K19/077 , G06N3/00 , G06T7/00 , G06V20/10 , H04R3/12 , G16H40/20 , G10L17/00 , G16Y20/00 , G06V20/52 , G06V40/16 , G06V40/20 , G06V40/10 , H04L51/222 , G06F18/25 , G16H50/30 , G16H80/00 , G16H30/00 , G16H40/63 , H04N7/18 , H04R3/00 , G16H10/20 , H04R1/32 , G16H15/00 , H04L51/02 , G16H40/60 , G16H30/20 , G16H30/40 , G10L21/0232 , G16H50/20 , G06N3/006 , G16B50/00 , G10L15/08 , G11B27/10 , H04R3/02 , G10L15/26 , H04R1/40 , G10L15/22 , G10L21/0208 , G10L15/18
CPC分类号: G16H10/60 , A61B5/7405 , G06F3/16 , G06F16/637 , G06F16/685 , G06F16/904 , G06F18/25 , G06F21/6245 , G06F40/174 , G06F40/30 , G06F40/40 , G06K19/07762 , G06N3/006 , G06T7/00 , G06V20/10 , G06V20/52 , G06V40/103 , G06V40/16 , G06V40/172 , G06V40/23 , G10L15/08 , G10L17/00 , G10L21/0232 , G11B27/10 , G16B50/00 , G16H10/20 , G16H15/00 , G16H30/00 , G16H30/20 , G16H30/40 , G16H40/20 , G16H40/60 , G16H40/63 , G16H50/20 , G16H50/30 , G16H80/00 , G16Y20/00 , H04L51/02 , H04L51/222 , H04N7/183 , H04R1/326 , H04R3/005 , H04R3/12 , G06T2207/10024 , G06T2207/10044 , G06T2207/10048 , G06T2207/10116 , G06T2207/10132 , G10L15/1815 , G10L15/22 , G10L15/26 , G10L2021/02082 , H04N7/181 , H04R1/406 , H04R3/02 , H04R2420/07 , H04S2400/15
摘要: A method, computer program product, and computing system for synchronizing machine vision and audio is executed on a computing device and includes obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information and audio encounter information. The machine vision encounter information and the audio encounter information are temporally-aligned to produce a temporarily-aligned encounter recording.
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公开(公告)号:US11847721B2
公开(公告)日:2023-12-19
申请号:US16623660
申请日:2018-06-21
申请人: Elekta AB (publ)
发明人: Jonas Anders Adler , Ozan Öktem
CPC分类号: G06T11/006 , G06T11/005 , G06T11/008 , G16H30/00 , G06T2210/41 , G06T2211/424
摘要: Much of the image processing that is applied to medical images is a form of “inverse problem”. This is a class of mathematical problems in which a “forward” model by which a signal is converted into dataset is known, to at least some degree, but where the aim is to reconstruct the signal given the resulting dataset. Thus, an inverse problem is essentially seeking to discover x given knowledge of A(x)+noise by finding an appropriate reconstruction operator A† such that A† (A(x)+noise)≈x, thereby enabling us to obtain x (or a close approximation) given knowledge of an output dataset consisting of A(x)+noise. Generally, several such processes (or their equivalents) are applied to the image dataset. If the first process (for example, noise reduction) is expressed via a first reconstruction operator A1† characterised by a parameter set Θ1 and the second process (for example, segmentation) is expressed via a second reconstruction operator A2† characterised by a parameter set Θ2, then the result of the two steps applied consecutively is A2† (A1†(y)). This can be expressed as an overall reconstruction operator P+, characterised by a parameter set Φ. If we then allow a machine learning process to optimise P+, then the steps previously carried out separately can be combined into a single optimisation. This yields advantages in terms of computational load and in the accuracy of the end result.
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