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Body part recognition model training method and system in CT images

A recognition model and model training technology, applied in the field of medical image recognition, can solve problems such as false detection of inspection parts, and achieve the effect of avoiding poor recognition accuracy

Active Publication Date: 2022-03-25
青岛美迪康数字工程有限公司
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  • Claims
  • Application Information

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Problems solved by technology

In the CT extremities inspection, the inspection part identification recorded in the generated Dicom file is the extremity, and the current part is not clearly identified as the left and right hands, left and right legs, left and right feet and other specific parts, which will cause false detection of the inspection parts

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  • Body part recognition model training method and system in CT images
  • Body part recognition model training method and system in CT images
  • Body part recognition model training method and system in CT images

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Embodiment Construction

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0024] In a first aspect, the present invention provides a method for training a body part recognition model in a CT image, see figure 1 , the method includes the following steps S110~S130:

[0025] S110, acquiring a CT positioning film image;

[0026] It is understandable that the CT image has corresponding basic information of the Dicom f...

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Abstract

The invention relates to the technical field of medical image recognition, and provides a method and system for training a body part recognition model in CT images. The method includes: obtaining CT positioning slice images; obtaining CT thin-slice sequence images, performing maximum density projection reconstruction on the CT thin-slice sequence images to obtain three-dimensional maximum density projection images; and generating multiple two-dimensional images corresponding to multiple viewing angles from the three-dimensional maximum density projection images. Maximum density projection images; model training was performed using CT positioning slice images and two-dimensional maximum density projection images to obtain a body part recognition model. The system includes a first acquisition module, a second acquisition module and a model training module. The invention supplements the training samples through the maximum density projection image to solve the problem of insufficient training samples.

Description

technical field [0001] The invention relates to the technical field of medical image recognition, in particular to a method and system for training a body part recognition model in CT images. Background technique [0002] The quality of medical imaging directly affects the doctor's diagnosis, and it is of great significance to check whether the body position is correct as the most basic content of the medical imaging quality evaluation standard. In the CT extremities inspection, the inspection site identification recorded in the generated Dicom file is the extremity, and the current site is not clearly identified as the left and right hands, left and right legs, left and right feet, etc., which will cause false detection of the inspection site. Contents of the invention [0003] In order to solve the above-mentioned technical problems or at least partly solve the above-mentioned technical problems, the present invention provides a method and system for training a body part...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00G06N3/04G06N3/08
CPCG06T11/003G06N3/04G06N3/084
Inventor 陈栋栋冯健赖永航曹鸥
Owner 青岛美迪康数字工程有限公司
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