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Calibrate the starting line of fat thickness on the image and the method of fat thickness measurement

A fat thickness and image technology, applied in the computer field, can solve problems such as unusable methods, unguaranteed calculation accuracy, and unintuitiveness, and achieve the effect of facilitating implementation, high accuracy, and simple processing steps

Active Publication Date: 2021-12-10
成都汇声科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The above-mentioned methods are all obtained by using ultrasonic simultaneous signals, and the calculation accuracy is not guaranteed, especially when they are separated from the ultrasonic equipment, the methods cannot be used and are not intuitive

Method used

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  • Calibrate the starting line of fat thickness on the image and the method of fat thickness measurement
  • Calibrate the starting line of fat thickness on the image and the method of fat thickness measurement
  • Calibrate the starting line of fat thickness on the image and the method of fat thickness measurement

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0072] The image of the present invention is an image obtained by ultrasonic equipment at the place where the body has fat. It is necessary to collect and process the ultrasonic image information first. To collect the ultrasonic image information, you can refer to the ultrasonic instrument device of the following Chinese patent CN209751086U, which can realize the acquisition of ultrasonic image information. And process ultrasound image information. refer to figure 1 .

[0073] This embodiment includes an ultrasonic transducer for sending out scanning beams, a digital control processing chip for controlling the ultrasonic transducer to send out scanning beams and collecting echo signals, and a digital control processing chip for sending control instructions to the digital control processing chip and viewing scanned images The portable control terminal, as well as the transmitting and receiving multiplexing circuit, the transmitting and receiving switching circuit, the transmit...

example 2

[0083] refer to figure 2 , the steps to calibrate the starting line of fat thickness on the image are as follows:

[0084] The first step is to import an image, and then start working on that image.

[0085] Perform Gaussian filtering on the imported image, and use a 3x3 Gaussian convolution kernel to perform convolution filtering on the image to blur the image, which is convenient for later gradient estimation and image segmentation processing. For the results, refer to image 3 .

[0086] 1. After Gaussian filtering, start to make image templates with strong edges, as follows:

[0087] (111). The Laplacian operator is used to calculate the edge image of the image, that is, the gradient image.

[0088] (112). The calculated edge image is absolute valued and normalized to be between 0-1. Specifically:

[0089] (113). A threshold value is used to perform threshold value processing on the edge image, and the threshold value can be set to 0.85. And after binarization, a bi...

example 3

[0101] refer to Figure 6 , when implementing Example 2, when performing the step of finding a connected domain whose length is greater than 50% of the image length, the preferred method is: enveloping the connected domain to obtain a circumscribing rectangle; calculating the length of the circumscribing rectangle. Firstly, the number of pixel columns occupied by the bounding rectangle is calculated, which is used for the total number of pixel columns of the entire image. For example, if the image has a total of 1080 pixel columns, and the circumscribed rectangular frame occupies 500 pixel columns, then this connected domain is not considered as a recognition area; while the image has a total of 1080 pixel columns, and the circumscribed rectangular frame occupies 550 pixel columns, then this connected domain is considered is the recognition area.

[0102]When implementing Example 2, when performing the step of finding a connected domain whose length is greater than 50% of the...

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Abstract

The invention discloses a fat thickness starting line marked on an image and a method for measuring the fat thickness, which is an image recognition technology. Wherein, the step of marking the starting line of fat thickness on the image is: in the image, find the connected domains of the color blocks, and among the found connected domains, find the connected domains whose length is greater than 50% of the length of the image as candidate connected domains. The identification area is found for the candidate connected domain, and the fat thickness starting line is in the identification area. Then the fat thickness is calculated through the fat thickness starting line and the lower boundary of the skin layer. The method provided by the invention can automatically identify the fat layer on the image, and calculate the fat thickness through the obtained fat layer.

Description

technical field [0001] The invention relates to a computer technology, especially a technology for processing ultrasonic images. Background technique [0002] In order to assist in the calculation of fat thickness, existing technical solutions such as: [0003] The fat content measuring system and method disclosed in patent CN106770647A is to calculate the fat thickness and fat content of the measured object according to the synthesized ultrasonic echoes. [0004] Patent CN106691512A discloses a method for estimating sampled tissue parameters and a system for multi-parameter evaluation of sampled tissue by obtaining ultrasonic echo signals from the first region of interest and the second region of interest in the sampled tissue, and One or more parameters of the sampled tissue are estimated using a reference phantom. [0005] The method and equipment disclosed in the patent CN1277007A for measuring human body fat distribution adopt the steps of measuring bioelectrical impe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/187G06T7/168G06T7/136G06T7/12G06T7/00A61B8/08
CPCG06T7/187G06T7/168G06T7/136G06T7/12G06T7/0012A61B8/0858A61B8/5223G06T2207/10132
Inventor 甘建红谭鑫
Owner 成都汇声科技有限公司
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