Medical image segmentation method and device, computer equipment and storage medium
A technology of medical imaging and computer programs, applied in medical images, neural learning methods, computer-aided medical procedures, etc., can solve the problems of labor cost reduction, difficulty in high-quality labeling, time-consuming, etc., and achieve the effect of saving labor costs
Active Publication Date: 2019-06-11
TENCENT TECH (SHENZHEN) CO LTD
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[0003] Traditional medical image segmentation methods require pixel / voxel-level annotation when training the mapping model, which is time-consuming, labor-intensive, and requires strong support from doctors. It is very difficult to obtain a large number of high-quality annotations
Therefore, the labor cost of traditional medical image segmentation needs to be further reduced
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[0032] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0033] figure 1 It is a schematic diagram of the application environment of the medical image segmentation method in one embodiment. The medical image segmentation method provided by this application can be applied to such as figure 1 shown in the application environment. Wherein, the terminal 102 communicates with the server 104 through the network. The medical image segmentation method of the embodiment of the present application can run on the server 104, and the terminal 102 can send medical image data, target objects and weakly supervised labeling information to th...
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The invention relates to a medical image segmentation method and device, computer equipment and a storage medium. The method comprises the following steps of obtaining a target object and weak supervision annotation information of the target object in the medical image data; determining a pseudo segmentation mask aiming at the target object in the medical image data according to the weak supervision annotation information; and performing mapping based on the pseudo segmentation mask, the medical image data and a preset mapping model to obtain a target segmentation result for the target object.Because the medical image data is segmented based on the weak supervised annotation information, when the preset mapping model adopted for mapping based on the pseudo segmentation mask and the medical image data is trained, a large amount of manual annotation information does not need to be adopted, so that the labor cost can be saved.
Description
technical field [0001] The present application relates to the field of medical image processing, in particular to a medical image segmentation method, device, computer equipment and storage medium. Background technique [0002] Medical imaging refers to internal tissue images of the human body or a part of the human body obtained in a non-invasive manner for medical treatment or medical research. Medical image segmentation plays an important role in clinical diagnostic decision-making, treatment planning, and intraoperative navigation. [0003] Traditional medical image segmentation methods require pixel / voxel-level annotation when training the mapping model, which is time-consuming, labor-intensive, and requires strong support from doctors. It is very difficult to obtain a large number of high-quality annotations. Therefore, the human cost of traditional medical image segmentation needs to be further reduced. Contents of the invention [0004] Based on this, it is neces...
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IPC IPC(8): G06T7/11G06T7/13G06N3/08
CPCG06T7/11G06N3/08G16H30/40G16H50/70G16H50/20G06T2207/20081G06T2207/20084G06T2207/20104G06T2207/30004G06N3/045
Inventor 曹世磊马锴郑冶枫
Owner TENCENT TECH (SHENZHEN) CO LTD