公开(公告)号：US12198407B2

公开(公告)日：2025-01-14

申请号：US17710254

申请日：2022-03-31

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： Han Zheng ,  Hong Shang ,  Xiaoning Wang ,  Jianhua Yao

IPC: G06V10/77 ,  G06V10/74 ,  G06V10/764 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82

Abstract: An artificial intelligence-based image processing method includes: obtaining a first sample image of a source domain and a second sample image of a target domain, the first sample image of the source domain carrying a corresponding target processing result; converting the first sample image into a target sample image, the target sample image carrying a corresponding target processing result; training a first image processing model based on the target sample image and the target processing result corresponding to the target sample image, to obtain a second image processing model; and inputting, in response to obtaining a human tissue image of the target domain, the human tissue image into the second image processing model, positioning, by the second image processing model, a target human tissue in the human tissue image, and outputting position information of the target human tissue in the human tissue image.

公开(公告)号：US11969145B2

公开(公告)日：2024-04-30

申请号：US17446095

申请日：2021-08-26

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： Zijian Zhang ,  Zhongqian Sun ,  Xinghui Fu ,  Hong Shang ,  Xiaoning Wang ,  Wei Yang

IPC: A61B1/00 ,  G06T7/00

CPC classification number: A61B1/000094 ,  A61B1/000096 ,  A61B1/0005 ,  G06T7/0012 ,  G06T2207/10068 ,  G06T2207/20024 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30092 ,  G06T2207/30096

Abstract: A medical endoscope image recognition method is provided. In the method, endoscope images are received from a medical endoscope. The endoscope images are filtered with a neural network, to obtain target endoscope images. Organ information corresponding to the target endoscope images is recognized via the neural network. An imaging type of the target endoscope images is identified according to the corresponding organ information with a classification network. A lesion region in the target endoscope images is localized according to an organ part indicated by the organ information. A lesion category of the lesion region in an image capture mode of the medical endoscope corresponding to the imaging type is identified.