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公开(公告)号:US11903646B2
公开(公告)日:2024-02-20
申请号:US15734237
申请日:2019-04-15
Applicant: Topcon Corporation
Inventor: Yusuke Ono
CPC classification number: A61B3/102 , A61B3/0025 , G06T7/0012 , G06T7/70 , G06T2207/10101 , G06T2207/30041 , G06T2207/30168 , G06V2201/03
Abstract: An ophthalmic apparatus of an embodiment example applies an OCT scan to an anterior segment and constructs an image from acquired data. Further, the ophthalmic apparatus analyzes the image to detect an artifact along an A-scan direction and moves an OCT optical system based on the artifact. Also, the ophthalmic apparatus analyzes the image to detect a corneal image and judges whether an intersection between the artifact and the corneal image is located within a predetermined area. In addition, the ophthalmic apparatus calculates an image quality evaluation value of the image, and controls the OCT optical system to perform an OCT scan of a predetermined pattern if the intersection is located within the area and the image quality evaluation value is equal to or greater than a predetermined threshold.
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公开(公告)号:US20240054761A1
公开(公告)日:2024-02-15
申请号:US17766439
申请日:2020-10-02
Applicant: New York Stem Cell Foundation, Inc.
Inventor: Brodie Fischbacher , Daniel John Paull , Zhongwei Wang
IPC: G06V10/764 , G06V10/20 , G06T7/11 , G06T11/60 , G06V10/82
CPC classification number: G06V10/764 , G06V10/255 , G06T7/11 , G06T11/60 , G06V10/82 , G06T2207/10016 , G06T2210/22 , G06T2207/20084 , G06T2207/10056 , G06T2207/30072 , G06V2201/03
Abstract: The present disclosure provides a system and method for image analysis which utilize trained neural networks. The system and method are useful for generation and/or analysis of a variety of objects, such as biological cells to determine clonality.
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353.
公开(公告)号:US20240054756A1
公开(公告)日:2024-02-15
申请号:US18550935
申请日:2022-03-15
Applicant: SUPERSONIC IMAGINE
Inventor: Bo ZHANG
CPC classification number: G06V10/60 , G06V10/48 , G06T15/06 , G06T15/08 , G06V2201/03
Abstract: The invention relates to for method for processing multi-modality and/or multi-source data of a medium, wherein said method may be implemented by a processing system, the method comprising the following steps:
an optical determination step in which for at least one of a plurality of volume units of the medium an optical property is determined based on the data of a modality and/or source,
a fluorescence determination step in which for at least one of the volume units a fluorescence property is determined based on the data of a second modality and/or source, and
a rendering step in which a data representation of the medium is rendered based on the determined optical and fluorescence properties of the volume units. The invention also relates to a corresponding processing system.-
公开(公告)号:US20240054638A1
公开(公告)日:2024-02-15
申请号:US18257797
申请日:2021-12-21
Applicant: Pulsemedica Corp.
Inventor: Christopher Ceroici , Nir Katchinskiy
IPC: G06T7/00 , G06V10/774 , G06V10/94 , G16H30/40
CPC classification number: G06T7/0012 , G06V10/774 , G06V10/945 , G16H30/40 , G06T2207/20081 , G06T2200/24 , G06T2207/20101 , G06V2201/03
Abstract: Features of a medical condition can be automatically annotated in medical images using a classification model that has been trained to classify images as having the medical condition or not. The automatically annotated features may be further processed to generate a treatment plan for treating the medical condition, for example with a laser, ultrasound, or other treatment method.
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公开(公告)号:US11896324B2
公开(公告)日:2024-02-13
申请号:US17746722
申请日:2022-05-17
Applicant: IX Innovation LLC
Inventor: Jeffrey Roh , Justin Esterberg , John Cronin , Seth Cronin , Michael John Baker
IPC: G10L15/22 , A61B34/00 , G16H50/20 , G16H50/50 , G10L15/26 , G10L15/30 , G10L13/02 , G10L15/06 , G06V10/40 , G06T7/00 , G16B20/20 , G16B40/20 , G16H10/60
CPC classification number: A61B34/25 , G06T7/0012 , G06V10/40 , G10L13/02 , G10L15/063 , G10L15/22 , G10L15/26 , G10L15/30 , G16B20/20 , G16B40/20 , G16H10/60 , G16H50/20 , G16H50/50 , A61B2034/256 , G06T2207/30004 , G06V2201/03
Abstract: Methods, apparatuses, and systems for transcribing and performing analysis on patient data are disclosed. Data is collected from one or more medical professionals as well as sensors and imaging devices positioned on or oriented towards a patient. An analysis is performed on the patient data and the data is presented to a medical professional via a verbal interface in a conversational manner, allowing the medical professional to provide additional data such as observations or instructions which may be used for further analysis or to perform actions related to the patient's care.
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公开(公告)号:US20240046555A1
公开(公告)日:2024-02-08
申请号:US18365140
申请日:2023-08-03
Applicant: Gustav LO
Inventor: Gustav LO
CPC classification number: G06T15/205 , G06T5/50 , G06V10/24 , G06V10/44 , G06V2201/03 , G06T2207/20221
Abstract: A system includes data processing hardware and memory hardware in communication with the data processing hardware. The memory hardware stores instructions that when executed by the data processing hardware perform operations. The operations include receiving a first image of an object captured by a first image capturing device at a first image capturing location, receiving a second image of the object captured by a second image capturing device at a second image capturing location, and receiving a third image of the object captured by a third image capturing device at a third image capturing location. The first, second, and third images comprise first, second, and third views, respectively. The operations also include generating a three-dimensional (3D) composite image from the first, second, and third images. Each of the first, second, and third image capturing locations are distinct locations that form a convex arc about the object.
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公开(公告)号:US20240037741A1
公开(公告)日:2024-02-01
申请号:US18360366
申请日:2023-07-27
Inventor: Ting-Ying Chien , Hsiao-Huang Chang
IPC: G06T7/00 , G06V10/764 , G06V10/10 , G06T7/70 , G06T7/11
CPC classification number: G06T7/0012 , G06V10/764 , G06V10/16 , G06T7/70 , G06T7/11 , G06V2201/03 , G06T2207/30108 , G06T2207/30048 , G06T2207/30021 , G06T2207/20081 , G06T2207/20084 , A61B6/481
Abstract: A cardiac catheterization image recognition and evaluation method is disclosed. The first deep learning algorithm is used to conduct an object recognition process on the cardiac catheterization image to obtain the vessel object image. The image processing process is conducted to the cardiac catheterization image to obtain the vessel location image. The vessel object image and the vessel location image are combined to obtain the vessel contour image. The vessel type judging process is conducted to the vessel contour image to determine the type of vessel in the cardiac catheterization image. The second deep learning algorithm is used on the vessel contour image to detect the vessel occlusion location and to judge the vessel occlusion rate. Based on the type of vessel and the vessel occlusion rate at the vessel occlusion location, the cardiac catheterization image is evaluated to obtain the SYNTAX Score.
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公开(公告)号:US20240033533A1
公开(公告)日:2024-02-01
申请号:US18258452
申请日:2021-12-20
Applicant: SOLENIC MEDICAL, INC.
Inventor: David Greenberg , John Tepper , Rajiv Chopra
CPC classification number: A61N2/004 , G06T7/74 , G06V10/751 , A61N2/02 , A61L27/04 , A61L27/50 , G16H30/40 , G06T2207/30004 , G06T2207/30204 , G06T2207/20092 , G06V2201/03 , A61L2430/24
Abstract: An embodiment includes: (1) determining a first orientation of first and second portions of a first image with respect to one another, wherein the first portion depicts a first metallic implant and the second portion depicts a first coil, wherein the first orientation is based on: (a) a first distance between the first and second portions with respect to one another, and (b) a first direction between the first and second portions with respect to one another; (2) select a first target orientation for the first metallic implant and the first coil with respect to one another from a library of target orientations between implants and coils; (3) determine a first difference between the first orientation and the first target orientation; and (4) output first reorientation instructions via the at least one I/O port in response to determining the first difference between the first orientation and the first target orientation.
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公开(公告)号:US11886543B2
公开(公告)日:2024-01-30
申请号:US17294731
申请日:2019-11-15
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor: Juergen Weese , Thomas Blaffert , Tom Brosch , Hans Barschdorf
IPC: G06F18/21 , G06N20/00 , G06F18/40 , G06F18/214
CPC classification number: G06F18/2178 , G06F18/2148 , G06F18/40 , G06N20/00 , G06V2201/03
Abstract: A system and computer-implemented method are provided for annotation of image data. A user is enabled to iteratively annotate the image data. An iteration of said iterative annotation comprises generating labels for a current image data part based on user-verified labels of a previous image data part, and enabling the user to verify and correct said generated labels to obtain user-verified labels for the current image data part. The labels for the current image data part are generated by combining respective outputs of a label propagation algorithm and a machine-learned classifier trained on user-verified labels and image data and applied to image data of the current image data part. The machine-learned classifier is retrained using the user-verified labels and the image data of the current image data part to obtain a retrained machine-learned classifier.
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公开(公告)号:US20240029404A1
公开(公告)日:2024-01-25
申请号:US18474252
申请日:2023-09-26
Applicant: FUJIFILM Corporation
Inventor: Hiroki WATANABE
IPC: G06V10/764 , A61B1/045 , A61B1/00 , A61B1/06
CPC classification number: G06V10/764 , A61B1/045 , A61B1/000094 , A61B1/0638 , A61B1/00048 , G06V2201/03
Abstract: An endoscope system that illuminates a subject and captures light from the subject acquires an examination image based on an image signal captured by an endoscope, divides the examination image into a plurality of regions as an input image, inputs the input image divided into the plurality of regions to a first classifier to output region evaluation values for the plurality of regions, and inputs an input image in which the region evaluation values are added to the plurality of regions to a second classifier to output a lesion evaluation value.
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