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Model training method, image processing method and device and electronic equipment

A training model and image processing technology, applied in the field of training models, can solve the problems of restricting the wide application of body composition analysis and low segmentation accuracy, and achieve the effect of improving processing effect and accuracy

Pending Publication Date: 2022-04-15
SHENZHEN INST OF ADVANCED TECH
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Problems solved by technology

[0003] At present, after obtaining the tomographic image, it is necessary to manually segment the distribution area of ​​tissues such as muscle and fat in the human body. Manual segmentation relies on subjective experience, and the accuracy of segmentation is low, which greatly limits the application of CT-based body composition analysis in medicine. widely used

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  • Model training method, image processing method and device and electronic equipment
  • Model training method, image processing method and device and electronic equipment
  • Model training method, image processing method and device and electronic equipment

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Embodiment Construction

[0035] 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.

[0036] Hereinafter, the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, a feature defined as "first" and "second" may explicitly or implicitly include one or more of these features. In the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more, and "at least one" and "one or more" mean one, two or more.

[0037] Reference to "one embodiment" or "s...

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Abstract

The embodiment of the invention provides a model training method and an image processing method, which are applied to the field of image processing, in particular to medical image processing, and in a model training process, an attention mechanism is added, and regions of human tissues are re-corrected in a weight form, so that the accuracy of image processing is improved. And the partial target weight of the current convolutional layer is greater than the preset weight of the previous convolutional layer, so that the processing effect of the target model is improved. In the image processing process, the target model is used for replacing traditional manual segmentation, and therefore automatic segmentation of the multiple human tissues in the CT image is achieved. According to the method provided by the embodiment of the invention, a plurality of human tissues can be segmented at one time, and the accuracy is improved.

Description

technical field [0001] The present application belongs to the field of image processing, and in particular relates to a method for training a model, an image processing method, device and electronic equipment. Background technique [0002] Body composition analysis is an analytical method that measures the proportion of body composition (mainly muscle and fat), and is often used to assess nutritional status, as well as obesity, metabolic diseases, cardiovascular diseases, hypertension, etc. Computer tomography (Computed Tomography, CT) is a common method for body composition analysis. CT scans the human body through X-rays to obtain tomographic images. The tomographic images can clearly show the distribution areas of tissues such as muscles and fat in the human body. The proportion of body composition is measured based on the distribution area of ​​tissues such as muscle and fat in the human body in the tomographic image. [0003] At present, after obtaining the tomographic...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/04G06N3/08
CPCG06N3/04G06T7/00G06N3/08
Inventor 申浩刘周胡战利何品任雅罗德红梁栋刘新郑海荣
Owner SHENZHEN INST OF ADVANCED TECH