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公开(公告)号:US11195052B2
公开(公告)日:2021-12-07
申请号:US16833451
申请日:2020-03-27
Applicant: COSMO ARTIFICIAL INTELLIGENCE—AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06K9/00 , G06K9/62 , A61B1/00 , A61B1/273 , G06N3/08 , G06T7/00 , G16H50/20 , G16H30/40 , A61B1/31 , G06N3/04
Abstract: The present disclosure relates to computer-implemented systems and methods for training and using generative adversarial networks to detect abnormalities in images of a human organ. In one implementation, a method is provided for training a neural network system, the method may include applying a perception branch of an object detection network to frames of a first subset of a plurality of videos to produce a first plurality of detections of abnormalities. Further, the method may include using the first plurality of detections and frames from a second subset of the plurality of videos to train a generator network to generate a plurality of artificial representations of polyps, and training an adversarial branch of the discriminator network to differentiate between artificial representations of the abnormalities and true representations of abnormalities. Additionally, the method may include retraining the perception branch based on difference indicators between the artificial representations of abnormalities and true representations of abnormalities included in frames of the second subset of plurality of videos and a second plurality of detections.
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公开(公告)号:US12089820B2
公开(公告)日:2024-09-17
申请号:US17251768
申请日:2019-06-11
Applicant: COSMO ARTIFICIAL INTELLIGENCE—AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06K9/00 , A61B1/00 , A61B1/31 , A61B5/00 , G06F18/214 , G06N3/045 , G06N3/08 , G06T7/00 , G06T7/70 , G06T11/00 , G06T11/20 , G06T11/60 , G06V10/20 , G06V10/25 , G06V10/82 , G06V20/40 , G16H30/20
CPC classification number: A61B1/31 , A61B1/000094 , A61B1/000095 , A61B1/000096 , A61B1/00055 , A61B5/7264 , A61B5/7267 , G06F18/214 , G06N3/045 , G06N3/08 , G06T7/0012 , G06T7/70 , G06T11/001 , G06T11/203 , G06T11/60 , G06V10/25 , G06V10/255 , G06V10/82 , G06V20/40 , G06V20/49 , G16H30/20 , G06T2207/10016 , G06T2207/10068 , G06T2207/20084 , G06T2207/30004 , G06T2207/30032 , G06T2207/30064 , G06T2207/30096 , G06V2201/03 , G06V2201/032
Abstract: The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display, and a third bus for directly transmitting the received real-time video to the output port.
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公开(公告)号:US11100633B2
公开(公告)日:2021-08-24
申请号:US16008015
申请日:2018-06-13
Applicant: Cosmo Artificial Intelligence—AI Limited
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06K9/00 , G06T7/00 , G06T7/70 , G16H30/20 , G06N3/08 , G06T11/00 , G06T11/60 , G06K9/32 , G06T11/20 , A61B1/00 , A61B5/00
Abstract: The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display, and a third bus for directly transmitting the received real-time video to the output port.
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公开(公告)号:US12299948B2
公开(公告)日:2025-05-13
申请号:US17794216
申请日:2021-01-29
Applicant: COSMO ARTIFICIAL INTELLIGENCE-AI LIMITED
Inventor: Andrea Cherubini , Nhan Ngo Dinh
Abstract: In one implementation, a computer-implemented system is provided for real-time video processing. The system includes at least one memory configured to store instructions and at least one processor configured to execute the instructions to perform operations. The at least one processor is configured to receive real-time video generated by a medical image system, the real-time video including a plurality of image frames, system. The at least processor is also configured to perform an object detection to detect and obtain context information indicating an interaction of a user with the medical image at least one object in the plurality of image frames and perform a classification to generate classification information for at least one object in the plurality of image frames. Further, the at least one processor is configured to perform a video manipulation to modify the received real-time video based on at least one of the object detection and the classification. Moreover, the processor is configured to invoke at least one of the object detection, the classification, and the video manipulation based on the context information.
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公开(公告)号:US12158924B2
公开(公告)日:2024-12-03
申请号:US17251773
申请日:2019-06-11
Applicant: COSMO ARTIFICIAL INTELLIGENCE—AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06F18/2413 , A61B1/00 , A61B1/273 , A61B1/31 , G06F18/21 , G06F18/214 , G06F18/40 , G06N3/045 , G06N3/08 , G06N3/088 , G06T7/00 , G16H30/40 , G16H50/20
Abstract: The present disclosure relates to computer-implemented systems and methods for training and using generative adversarial networks. In one implementation, a system for training a generative adversarial network may include at least one processor that may provide a first plurality of images including representations of a feature-of-interest and indicators of locations of the feature-of-interest and use the first plurality and indicators to train an object detection network. Further, the processor(s) may provide a second plurality of images including representations of the feature-of-interest, and apply the trained object detection network to the second plurality to produce a plurality of detections of the feature-of-interest. Additionally, the processor(s) may provide manually set verifications of true positives and false positives with respect to the plurality of detections, use the verifications to train a generative adversarial network, and retrain the generative adversarial network using at least one further set of images, further detections, and further manually set verifications.
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公开(公告)号:US11574403B2
公开(公告)日:2023-02-07
申请号:US17379902
申请日:2021-07-19
Applicant: COSMO ARTIFICIAL INTELLIGENCE—AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06K9/62 , G06T7/00 , G06T7/70 , G16H30/20 , G06N3/08 , G06T11/00 , G06T11/60 , G06T11/20 , A61B1/00 , A61B5/00 , G06V10/25 , G06V10/20 , G06V20/40 , G06N3/04 , G06V10/82
Abstract: The present disclosure relates to computer-implemented systems and methods for detecting a feature-of-interest in a video. In one implementation, a computer-implemented system may include a discriminator network and a generative network. The discriminator network may include a perception branch and an adversarial branch, the perception branch being configured to output detections of the feature-of-interest in the video. The generative network may be configured to receive detections of the feature-of-interest from the perception branch of the discriminator network and generate artificial representations of the feature-of-interest based on the detections from the perception branch. Further, the adversarial branch may be configured to provide an output identifying differences between the false representations and true representations of the feature-of-interest, and the perception branch may be further configured to be trained by the output of the adversarial branch so that false representations are not detected by the perception branch as true representations.
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公开(公告)号:US12207798B2
公开(公告)日:2025-01-28
申请号:US18525800
申请日:2023-11-30
Applicant: COSMO ARTIFICIAL INTELLIGENCE—AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06K9/62 , A61B1/00 , A61B1/31 , A61B5/00 , G06F18/214 , G06N3/045 , G06N3/08 , G06T7/00 , G06T7/70 , G06T11/00 , G06T11/20 , G06T11/60 , G06V10/20 , G06V10/25 , G06V10/82 , G06V20/40 , G16H30/20
Abstract: The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display, and a third bus for directly transmitting the received real-time video to the output port.
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公开(公告)号:US12190512B2
公开(公告)日:2025-01-07
申请号:US17961764
申请日:2022-10-07
Applicant: Cosmo Artificial Intelligence—AI Limited
Inventor: Andrea Cherubini , Pietro Salvagnini , Nhan Ngo Dinh
Abstract: A computer-implemented system is provided that includes at least one processor that is adapted to analyze a plurality of frames from a real-time video to identify frames during which an operator is interacting with an image device to examine areas of a patient. The at least one processor is further configured to generate, from the identified frames, data representations of a first area examined by the operator interacting with the image device and further generate data representations of one or more further areas examined by the operator interacting with the image device. The at least one processor is also configured to aggregate the data representations of the first area with the data representations of the one or more further areas and determine, using the aggregated data representations, an examination quality level of the areas examined by the operator and present, on a display device during the medical procedure, a graphical representation indicating the examination quality level of the areas examined by the operator.
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公开(公告)号:US20210343013A1
公开(公告)日:2021-11-04
申请号:US17379902
申请日:2021-07-19
Applicant: COSMO ARTIFICIAL INTELLIGENCE - AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06T7/00 , G06T7/70 , G16H30/20 , G06N3/08 , G06T11/00 , G06T11/60 , G06K9/00 , G06K9/32 , G06T11/20 , A61B1/00 , A61B5/00
Abstract: The present disclosure relates to computer-implemented systems and methods for detecting a feature-of-interest in a video. In one implementation, a computer-implemented system may include a discriminator network and a generative network. The discriminator network may include a perception branch and an adversarial branch, the perception branch being configured to output detections of the feature-of-interest in the video. The generative network may be configured to receive detections of the feature-of-interest from the perception branch of the discriminator network and generate artificial representations of the feature-of-interest based on the detections from the perception branch. Further, the adversarial branch may be configured to provide an output identifying differences between the false representations and true representations of the feature-of-interest, and the perception branch may be further configured to be trained by the output of the adversarial branch so that false representations are not detected by the perception branch as true representations.
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公开(公告)号:US12161305B2
公开(公告)日:2024-12-10
申请号:US18165180
申请日:2023-02-06
Applicant: COSMO ARTIFICIAL INTELLIGENCE—AI LIMITED
Inventor: Nhan Ngo Dinh , Giulio Evangelisti , Flavio Navari
IPC: G06K9/00 , A61B1/00 , A61B1/31 , A61B5/00 , G06F18/214 , G06N3/045 , G06N3/08 , G06T7/00 , G06T7/70 , G06T11/00 , G06T11/20 , G06T11/60 , G06V10/20 , G06V10/25 , G06V10/82 , G06V20/40 , G16H30/20
Abstract: The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display, and a third bus for directly transmitting the received real-time video to the output port.
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