公开(公告)号：US20230360776A1

公开(公告)日：2023-11-09

申请号：US18038112

申请日：2021-11-23

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： HONGXIN CHEN ,  JIAYIN ZHOU ,  SA YUAN LIANG ,  YI FAN

IPC: G06V10/80 ,  G16H30/40 ,  G06V10/82

CPC classification number: G16H30/40 ,  G06V10/80 ,  G06V10/82 ,  G06V2201/031 ,  G06V2201/032

Abstract: A method and system for image feature classification using a NN-based learning algorithms to make a decision about a feature in a medical image or image part. In particular, embodiments may make use of a phase of a multi-phasic image to improve classification accuracy. For instance, embodiments may combine different phases of multiphasic images as training data.

公开(公告)号：US20230334666A1

公开(公告)日：2023-10-19

申请号：US17952234

申请日：2022-09-24

Applicant: PSIP LLC

Inventor： Salmaan HAMEED ,  Giau NGUYEN

IPC: G06T7/00 ,  G01B11/30 ,  G01B11/03 ,  G06V10/50 ,  G06V10/44 ,  A61B1/00

CPC classification number: G06T7/0014 ,  G01B11/30 ,  G01B11/03 ,  G06V10/50 ,  G06V10/454 ,  A61B1/000094 ,  A61B1/000096 ,  A61B1/0014 ,  A61B1/00177 ,  A61B1/00181 ,  G06V2201/032 ,  G06V2201/034 ,  A61B1/00101 ,  G06K9/6273

Abstract: Identifying polyps or lesions in a colon. In some variations, computer-implemented methods for polyp detection may be used in conjunction with an endoscope system to analyze the images captured by the endoscopic system, identify any polyps and/or lesions in a visual scene captured by the endoscopic system, and provide an indication to the practitioner that a polyp and/or lesion has been detected.

公开(公告)号：US20230298306A1

公开(公告)日：2023-09-21

申请号：US18021242

申请日：2021-09-01

Applicant: Given Imaging LTD.

Inventor： Dorit Baras ,  Eyal Dekel

IPC: G06V10/74 ,  G06T7/00

CPC classification number: G06V10/74 ,  G06T7/0012 ,  G06T2207/20084 ,  G06V2201/032

Abstract: The present disclosure relates to systems and methods for determining whether two images of a gastrointestinal tract (GIT) contain the same occurrence of an event indicator or different occurrences of an event indicator. An exemplary processing system includes at least one processor and at least one memory storing instructions. When the instruction are executed by the processor(s), they cause the processing system to access a first image and a second image of a portion of a GIT, where the first image and the second image contain at least one occurrence of an event indicator, and to classify the first image and the second image by a classification system configured to provide an indication of whether the first image and second image contain a same occurrence of the event indicator or contain different occurrences of the event indicator.

公开(公告)号：US20230263384A1

公开(公告)日：2023-08-24

申请号：US18165232

申请日：2023-02-06

Applicant: COSMO ARTIFICIAL INTELLIGENCE - AI LIMITED

Inventor： NHAN NGO DINH ,  GIULIO EVANGELISTI ,  FLAVIO NAVARI

IPC: A61B1/31 ,  G06T11/60 ,  A61B1/00 ,  G06N3/08 ,  A61B5/00 ,  G06V10/25 ,  G06V20/40 ,  G06T11/20 ,  G06V10/82 ,  G06V10/20 ,  G06T11/00 ,  G16H30/20 ,  G06T7/70 ,  G06T7/00

CPC classification number: A61B1/31 ,  G06T11/60 ,  A61B1/000095 ,  G06N3/045 ,  G06N3/08 ,  A61B5/7264 ,  G06V10/25 ,  A61B5/7267 ,  A61B1/000096 ,  G06V20/49 ,  A61B1/00055 ,  G06T11/203 ,  G06V10/82 ,  G06V20/40 ,  G06V10/255 ,  G06F18/214 ,  G06T11/001 ,  G16H30/20 ,  A61B1/000094 ,  G06T7/70 ,  G06T7/0012 ,  G06T2207/10068 ,  G06T2207/20084 ,  G06V2201/032 ,  G06T2207/30064 ,  G06T2207/10016 ,  G06T2207/30032 ,  G06T2207/30004 ,  G06V2201/03 ,  G06T2207/30096

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.

公开(公告)号：US11730439B2

公开(公告)日：2023-08-22

申请号：US17506507

申请日：2021-10-20

Applicant: Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

Inventor： Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

IPC: A61B6/00 ,  A61B6/02 ,  G06T17/00 ,  G01N23/044 ,  A61B6/03 ,  A61B6/06 ,  G01N23/083 ,  G01N23/18 ,  G06T7/00 ,  G06T11/00 ,  A61B6/04 ,  G06T7/11 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  G06V10/25 ,  G06V10/62 ,  A61B6/08

CPC classification number: A61B6/541 ,  A61B6/025 ,  A61B6/032 ,  A61B6/035 ,  A61B6/0407 ,  A61B6/06 ,  A61B6/08 ,  A61B6/405 ,  A61B6/4007 ,  A61B6/4014 ,  A61B6/4021 ,  A61B6/4208 ,  A61B6/4283 ,  A61B6/4405 ,  A61B6/4441 ,  A61B6/4452 ,  A61B6/4476 ,  A61B6/4482 ,  A61B6/467 ,  A61B6/482 ,  A61B6/54 ,  A61B6/542 ,  A61B6/56 ,  A61B6/583 ,  G01N23/044 ,  G01N23/083 ,  G01N23/18 ,  G06T7/0012 ,  G06T7/0016 ,  G06T7/11 ,  G06T11/003 ,  G06T11/006 ,  G06T17/00 ,  G06V10/25 ,  G06V10/62 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  A61B6/4275 ,  A61B6/502 ,  G01N2223/401 ,  G06T2200/24 ,  G06T2207/10076 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30064 ,  G06T2207/30096 ,  G06T2207/30168 ,  G06T2210/41 ,  G06V2201/032

Abstract: An X-ray imaging system using multiple pulsed X-ray sources in motion to perform high efficient and ultrafast 3D radiography using an X-ray flexible curved panel detector is presented. There are multiple pulsed X-ray sources mounted on a structure in motion to form an array of sources. The sources move simultaneously relative to an object on a predefined arc track at a constant speed as a group. Each individual X-ray source can move around its static position at a small distance. When an individual source has a speed equal to group speed, but with opposite moving direction, the individual source and detector are activated. This allows source to stay relatively standstill during activation. The operation results in reduced source travel distance for each individual source. 3D radiography image data can be acquired with much wider sweep angle in much shorter time, and image analysis can also be done in real-time.

公开(公告)号：US20230255584A1

公开(公告)日：2023-08-17

申请号：US18124472

申请日：2023-03-21

Applicant: Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

Inventor： Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

IPC: A61B6/00 ,  A61B6/02 ,  G06T17/00 ,  G01N23/044 ,  A61B6/03 ,  A61B6/06 ,  G01N23/083 ,  G01N23/18 ,  G06T7/00 ,  G06T11/00 ,  A61B6/04 ,  G06T7/11 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  G06V10/25 ,  G06V10/62 ,  A61B6/08

CPC classification number: A61B6/541 ,  A61B6/025 ,  G06T17/00 ,  A61B6/4007 ,  A61B6/4283 ,  A61B6/4405 ,  A61B6/4482 ,  A61B6/542 ,  G01N23/044 ,  A61B6/032 ,  A61B6/06 ,  A61B6/4452 ,  A61B6/4476 ,  A61B6/467 ,  A61B6/56 ,  A61B6/583 ,  G01N23/083 ,  G01N23/18 ,  G06T7/0012 ,  G06T11/006 ,  A61B6/035 ,  A61B6/4014 ,  A61B6/4441 ,  A61B6/482 ,  A61B6/0407 ,  A61B6/4208 ,  G06T7/11 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  G06V10/25 ,  G06V10/62 ,  G06T7/0016 ,  A61B6/08 ,  A61B6/4021 ,  A61B6/54 ,  G06T11/003 ,  A61B6/405 ,  G06T2210/41 ,  G01N2223/401 ,  G06T2200/24 ,  G06T2207/10081 ,  G06T2207/20084 ,  G06T2207/30096 ,  A61B6/4275 ,  G06V2201/032 ,  G06T2207/10076 ,  G06T2207/20081 ,  G06T2207/30064 ,  G06T2207/30168 ,  A61B6/502

Abstract: An X-ray imaging system using multiple pulsed X-ray sources to perform highly efficient and ultrafast 3D radiography is presented. There are multiple pulsed X-ray sources mounted on a structure in motion to form an array of sources. The multiple X-ray sources move simultaneously relative to an object on a pre-defined arc track at a constant speed as a group. Electron beam inside each individual X-ray tube is deflected by magnetic or electrical field to move focal spot a small distance. When focal spot of an X-ray tube beam has a speed that is equal to group speed but with opposite moving direction, the X-ray source and X-ray flat panel detector are activated through an external exposure control unit so that source tube stay momentarily standstill equivalently. 3D scan can cover much wider sweep angle in much shorter time and image analysis can also be done in real-time.

公开(公告)号：US12102469B2

公开(公告)日：2024-10-01

申请号：US18514345

申请日：2023-11-20

Applicant: Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

Inventor： Jianqiang Liu ,  Manat Maolinbay ,  Chwen-yuan Ku ,  Linbo Yang

IPC: A61B6/00 ,  A61B6/02 ,  A61B6/03 ,  A61B6/04 ,  A61B6/06 ,  A61B6/08 ,  A61B6/40 ,  A61B6/42 ,  A61B6/46 ,  A61B6/58 ,  G01N23/044 ,  G01N23/083 ,  G01N23/18 ,  G06T7/00 ,  G06T7/11 ,  G06T11/00 ,  G06T17/00 ,  G06V10/25 ,  G06V10/62 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  A61B6/50

CPC classification number: A61B6/541 ,  A61B6/025 ,  A61B6/032 ,  A61B6/035 ,  A61B6/0407 ,  A61B6/06 ,  A61B6/08 ,  A61B6/4007 ,  A61B6/4014 ,  A61B6/4021 ,  A61B6/405 ,  A61B6/4208 ,  A61B6/4283 ,  A61B6/4405 ,  A61B6/4441 ,  A61B6/4452 ,  A61B6/4476 ,  A61B6/4482 ,  A61B6/467 ,  A61B6/482 ,  A61B6/54 ,  A61B6/542 ,  A61B6/56 ,  A61B6/583 ,  G01N23/044 ,  G01N23/083 ,  G01N23/18 ,  G06T7/0012 ,  G06T7/0016 ,  G06T7/11 ,  G06T11/003 ,  G06T11/006 ,  G06T17/00 ,  G06V10/25 ,  G06V10/62 ,  G16H10/60 ,  G16H30/20 ,  G16H50/20 ,  A61B6/4275 ,  A61B6/502 ,  G01N2223/401 ,  G06T2200/24 ,  G06T2207/10076 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30064 ,  G06T2207/30096 ,  G06T2207/30168 ,  G06T2210/41 ,  G06V2201/032

Abstract: An X-ray imaging system using multiple pulsed X-ray sources to perform highly efficient and ultrafast 3D radiography is presented. There are multiple pulsed X-ray sources mounted on a structure in motion to form an array of sources. The multiple X-ray sources move simultaneously relative to an object on a pre-defined arc track at a constant speed as a group. Electron beam inside each individual X-ray tube is deflected by magnetic or electrical field to move focal spot a small distance. When focal spot of an X-ray tube beam has a speed that is equal to group speed but with opposite moving direction, the X-ray source and X-ray flat panel detector are activated through an external exposure control unit so that source tube stay momentarily standstill equivalently. 3D scan can cover much wider sweep angle in much shorter time and image analysis can also be done in real-time.

公开(公告)号：US20240303299A1

公开(公告)日：2024-09-12

申请号：US18652226

申请日：2024-05-01

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

CPC classification number: G06F18/2413 ,  A61B1/000096 ,  A61B1/273 ,  A61B1/2736 ,  A61B1/31 ,  G06F18/214 ,  G06F18/2148 ,  G06F18/217 ,  G06F18/41 ,  G06N3/045 ,  G06N3/08 ,  G06N3/088 ,  G06T7/0012 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30032 ,  G06T2207/30096 ,  G06V2201/032

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 representation 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 tr 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.

公开(公告)号：US20240296560A1

公开(公告)日：2024-09-05

申请号：US18578337

申请日：2022-07-12

Applicant: COSMO ARTIFICIAL INTELLIGENCE – AI LIMITED

Inventor： ANDREA CHERUBINI ,  PIETRO SALVAGNINI ,  CARLO BIFFI ,  NHAN NGO DINH

IPC: G06T7/00 ,  A61B1/00 ,  G06T7/60 ,  G06T7/73 ,  G06V10/764 ,  G06V10/82 ,  G06V20/40 ,  G06V20/50 ,  G16H70/20

CPC classification number: G06T7/0012 ,  A61B1/000094 ,  G06T7/60 ,  G06T7/73 ,  G06V10/764 ,  G06V10/82 ,  G06V20/46 ,  G06V20/50 ,  G16H70/20 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20084 ,  G06T2207/30032 ,  G06T2207/30096 ,  G06V2201/032

Abstract: A computer-implemented system is provided that receives a real-time video captured from a medical image device during a medical procedure. The real-time video may include a plurality of frames. The system may be adapted to detect an object of interest in the plurality of frames and apply one or more neural networks configured to identify a plurality of characteristics of the detected object of interest, such as classification, size, and/or location. In some embodiments, the system is adapted to identify, based on one or more of the plurality of characteristics, a medical guideline and present, in real-time on a display device during the medical procedure, information for the medical guideline.

公开(公告)号：US20240249515A1

公开(公告)日：2024-07-25

申请号：US18626165

申请日：2024-04-03

Applicant: Tencent Technology (Shenzhen) Company Limited

Inventor： Zhongyi YANG ,  Sen YANG ,  Jinxi XIANG ,  Jun ZHANG ,  Xiao HAN

IPC: G06V10/82 ,  G06T7/00

CPC classification number: G06V10/82 ,  G06T7/0012 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06V2201/032

Abstract: A method for training an image recognition model is performed by a computer device. The method includes: obtaining a sample image and a corresponding sample label; obtaining a sample image patch bag of sample image patches corresponding to the sample image, the sample patch bag having a bag label corresponding to the sample label of the sample image; performing feature analysis on the sample patch bag and the sample image patches in the sample patch bag, respectively, by using an image recognition model; determining a relative entropy loss, a first cross entropy loss corresponding to the sample patch bag and a second cross entropy loss corresponding to the sample image patches based on corresponding bag feature analysis and patch analysis results, respectively; and training the image recognition model based on the relative entropy loss, the first cross entropy loss, and the second cross entropy loss.