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1.发明公开公开(公告)号：US20240212165A1
公开(公告)日：2024-06-27
申请号：US18437357
申请日：2024-02-09
Inventor： Liang WANG , Jun ZHANG
CPC classification number: G06T7/149 , G06T7/11 , G06T2207/10028 , G06T2207/20081 , G06T2207/30004
Abstract: The present disclosure provides a medical image segmentation method. The medical image segmentation method includes acquiring a to-be-processed medical image set, the to-be-processed medical image set including a plurality of to-be-processed medical images corresponding to different time points, processing the to-be-processed medical image set in a time dimension according to the to-be-processed medical images and the time points corresponding to the to-be-processed medical images to obtain a temporal dynamic image, and extracting a target region feature from the temporal dynamic image by using a medical image segmentation model, to acquire a target region.
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公开(公告)号：US20220207744A1
公开(公告)日：2022-06-30
申请号：US17697689
申请日：2022-03-17
Abstract: The disclosure provides an image processing method and apparatus. The method may include acquiring a target image having at least two division regions. The division region includes an annotation point, and the annotation point is corresponding to a target segmentation object. The method may further include performing iterative expansion on the annotation points to obtain an iterative expansion region. The method may further include determining a first loss result between the iterative expansion region and the division region and a second loss result between the iterative expansion region and the annotation point. The method may further include, when the first loss result and the second loss result meeting a termination condition, stopping the iterative expansion to obtain a resulting iterative expansion region. The method may further include determining the resulting iterative expansion region as a region where the target segmentation object is located in the target image.
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公开(公告)号：US20180290053A1
公开(公告)日：2018-10-11
申请号：US16006437
申请日：2018-06-12
Inventor： Jun ZHANG , Yipeng ZHAO , Luxi CHEN , Mingwei ZHANG , Yunhui YUAN , Xin ZHOU , Jianyang WEI , Yulin HUANG , Jiaxing LI
Abstract: A cross-platform game battle method and apparatus, a terminal, and a system are provided. The method includes sending a first request to a game server in response to a first operation, with respect to a game, on a first web page. A first response is received in response to the first request, and a game address is obtained according to the first response. The game address is sent to a second terminal, the game address being usable by the second terminal to obtain a second web page to start the game. The second terminal is on a platform that is different from a platform of the first web page.
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公开(公告)号：US20180043264A1
公开(公告)日：2018-02-15
申请号：US15791363
申请日：2017-10-23
Inventor： Min YAN , Yiping GUO , Jianghao ZHU , Siquan CHEN , Jun ZHANG , Yong FAN , Jun YUAN , Xin ZHANG
IPC: A63F13/71 , A63F13/213 , A63F13/30 , H04L29/06 , A63F13/533
CPC classification number: A63F13/71 , A63F13/213 , A63F13/30 , A63F13/533 , H04L67/38 , H05K999/99
Abstract: A method including generating, by a terminal, a creation request containing game information, sending, by the terminal, the creation request to a game server, receiving, by the terminal, a graphic information code generated by a management server according to the game information, and displaying the graphic information code on the terminal.
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公开(公告)号：US20240355025A1
公开(公告)日：2024-10-24
申请号：US18761158
申请日：2024-07-01
Inventor： Yingjie MEI , Meng WEI , Xianqi JING , Lili HAO , Xingyu XIAO , Hongjiang WANG , Ruowei JIANG , Jun ZHANG , Xiaogiang HONG , Lichao WU
IPC: G06T13/00 , A63F13/30 , A63F13/53 , G06F3/04817
CPC classification number: G06T13/00 , A63F13/30 , A63F13/53 , G06F3/04817
Abstract: This application provides an inter-account interaction method performed by a computer device. The method includes: displaying a battle preparation interface of a virtual battle, the battle preparation interface comprising a first icon representing a first account associated with the computer device and at least one second icon representing an account other than the first account; in response to a trigger operation on one of the at least one second icon as a target icon, displaying a prop selection area on the battle preparation interface and at least one interactive prop owned by the first account in the prop selection area; and in response to a selection of one of the at least one interactive prop as a target interactive prop, playing a target special effect animation of transmitting a special effect resource of the target interactive prop pointing from the first icon to the target icon.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240249411A1
公开(公告)日：2024-07-25
申请号：US18626197
申请日：2024-04-03
CPC classification number: G06T7/0012 , G06T7/11 , G06T7/77 , G06T7/90 , G16H30/40 , G06T2207/10024 , G06T2207/10056 , G06T2207/20081 , G06T2207/30024 , G06T2207/30242
Abstract: This application discloses a physiological image processing method performed by a computer device. The method includes: obtaining a physiological image; determining position information of at least one mutated object in the physiological image based on a physiological image processing model; performing color channel decomposition on the physiological image to obtain staining information corresponding to the physiological image; and making statistics according to the position information and the staining information to obtain a staining counting result of the mutated objects. According to this application, by obtaining the staining counting result of the mutated objects according to the position information of the mutated objects and the staining information, the staining counting result of the mutated objects is quickly obtained.
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公开(公告)号：US20230058876A1
公开(公告)日：2023-02-23
申请号：US17980439
申请日：2022-11-03
Abstract: An image processing method includes: acquiring a standard image matched with an image processing model; determining light field variation parameters of a use environment of the image processing model based on the standard image; determining an image training sample set based on the light field variation parameters, the image training sample set including images of different light field backgrounds; training a correction network of the image processing model through the image training sample set to obtain a model updating parameter adapted to the correction network, and generating a trained image processing model based on the model updating parameter; acquiring a single image in the use environment, and performing prediction processing on the single image through the trained image processing model to obtain light field information corresponding to the single image; and correcting a light field of the single image based on the light field information.
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公开(公告)号：US20240273721A1
公开(公告)日：2024-08-15
申请号：US18642802
申请日：2024-04-22
Inventor： Sen YANG , Jinxi XIANG , Jun ZHANG , Xiao HAN
IPC: G06T7/00 , G06F16/583 , G06V10/44 , G06V10/74 , G06V10/762
CPC classification number: G06T7/0012 , G06F16/583 , G06V10/44 , G06V10/761 , G06V10/762 , G06T2207/20132 , G06T2207/30024
Abstract: A whole slide image (WSI) search method is performed by a computer device, which belong to the field of artificial intelligence. The method includes: acquiring a plurality of tissue images obtained by cropping a WSI; inputting the plurality of tissue images into an image encoder to obtain image feature vectors respectively corresponding to the plurality of tissue images; determining at least one key image from the image feature vectors respectively corresponding to the plurality of tissue images; querying, based on image feature vectors respectively corresponding to the at least one key image, a database for at least one candidate image package respectively corresponding to the at least one key image; and determining at least one screened image package from the at least one candidate image package according to attributes of the at least one candidate image package as search results corresponding to the WSI.
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公开(公告)号：US20240273134A1
公开(公告)日：2024-08-15
申请号：US18642807
申请日：2024-04-22
Inventor： Sen YANG , Jinxi XIANG , Jun ZHANG , Xiao HAN
IPC: G06F16/535 , G06F16/55 , G06F16/56 , G06V10/26 , G06V10/46 , G06V10/74 , G06V10/762 , G06V10/764 , G06V10/774
CPC classification number: G06F16/535 , G06F16/55 , G06F16/56 , G06V10/26 , G06V10/46 , G06V10/761 , G06V10/762 , G06V10/764 , G06V10/774 , G06V2201/03
Abstract: Provided is a method for searching for a whole slide image performed by a computer device, which relate to the field of artificial intelligence. The method includes: cropping a whole slide image into a plurality of tissue images; generating, through an image encoder, image feature vectors respectively corresponding to the plurality of tissue images; clustering the image feature vectors respectively corresponding to the plurality of tissue images, to determine at least one key image from the plurality of tissue images; querying, based on image feature vectors respectively corresponding to the at least one key image, a database to obtain at least one target image package corresponding to the at least one key image; and determining a whole slide image to which at least one candidate tissue image comprised in the at least one target image package respectively belongs as a final search result.
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公开(公告)号：US20210350537A1
公开(公告)日：2021-11-11
申请号：US17383359
申请日：2021-07-22
Inventor： Liang WANG , Jun ZHANG
Abstract: An image processing method includes: obtaining DCE magnetic resonance images corresponding to a plurality of time points for a same detection target; determining average pixel grayscale values of images of a same lesion region in the DCE magnetic resonance images of the plurality of time points respectively; determining a time to peak according to the average pixel grayscale values corresponding to the plurality of time points; and generating a first-stage time-intensity image before the time to peak and a second-stage time-intensity image after the time to peak respectively according to the DCE magnetic resonance images and the time to peak. The first-stage time-intensity image and the second-stage time-intensity image are 3D images. A pixel grayscale value of each pixel in the first-stage time-intensity image and the second-stage time-intensity image represents a change rate of blood supply intensity and reflects a severity level of a lesion corresponding to the lesion region.
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