Multi-component semantic segmentation method based on four-cavity heart tangent plane of multi-disease fetus

A semantic segmentation and multi-component technology, applied in computer components, neural learning methods, biological neural network models, etc., can solve the problem of multi-disease multi-component segmentation, multi-component segmentation method without fetal four-chamber heart view, etc. problem, to achieve the effect of improving the segmentation evaluation index, improving the segmentation effect, and improving the segmentation result

Pending Publication Date: 2020-09-25
BEIHANG UNIV
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Problems solved by technology

[0003] However, at present, more studies are based on adult echocardiography, and research on the left atrial LV; although some studies have shown that the segmentation of the adult LV and the segmentation based on the four-chamber view have been used. Segmentation of the left atrium LV is performed on four-chamber cardiac images at end-systole ES and end-diastole ED; however, there is still no solution for multi-disease and multi-component segmentation, and there is no multi-component segmentation method for multi-disease fetal four-chamber view

Method used

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  • Multi-component semantic segmentation method based on four-cavity heart tangent plane of multi-disease fetus
  • Multi-component semantic segmentation method based on four-cavity heart tangent plane of multi-disease fetus
  • Multi-component semantic segmentation method based on four-cavity heart tangent plane of multi-disease fetus

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Embodiment 1

[0037] Such as figure 1 Shown: a multi-component semantic segmentation method based on multi-disease fetal four-chamber view, said method comprises the following steps:

[0038] A multi-component semantic segmentation method based on the multi-disease fetal four-chamber view, the method comprises the following steps:

[0039] (1), collecting echocardiographic sequence images;

[0040] (2), duplicating and expanding the sample size of the multi-position echocardiographic sequence images collected;

[0041] (3) Divide the sample size.

Embodiment 2

[0043] Such as figure 2 Shown: a multi-component semantic segmentation method based on multi-disease fetal four-chamber view, said method comprises the following steps:

[0044] (1), collecting echocardiographic sequence images;

[0045] (2), duplicating and expanding the sample size of the multi-position echocardiographic sequence images collected;

[0046] (3) Divide the sample size;

[0047] (4) Optimize the segmentation results.

Embodiment 3

[0049] Such as image 3 Shown: a multi-component semantic segmentation method based on multi-disease fetal four-chamber view, said method comprises the following steps:

[0050] (1) Acquisition of multi-position echocardiographic sequence images expanded by data enhancement strategy through fetal echocardiography;

[0051] (2) The input echocardiographic sequence images of multiple body positions are copied to expand the sample size and increase the proportion through the proportion balance strategy;

[0052] (3), the sample size is segmented by the cascaded network semantic segmentation method;

[0053] (4) Through a loss function optimization method; to obtain a better segmentation effect of the four-chamber heart view.

[0054] Such as Figure 4-7 Shown: The data enhancement strategy is to expand the fetal heart multi-position scene by means of rotation, translation and symmetry. The rotation includes expanding the image by 30°, 60° or 120° rotation; the translation inc...

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Abstract

The invention discloses a multi-component semantic segmentation method based on a four-cavity cardiac tangent plane of a multi-disease fetus. The method comprises the steps of collecting an ultrasoniccardiac sequence image, copying and expanding the sample size of the collected multi-position ultrasonic cardiac sequence image, and segmenting the sample size; segmenting the plurality of componentsbased on the four-cavity heart tangent planes of the plurality of disease types; using a proportion balance strategy to obtain a better segmentation effect, especially in a group with a low data volume proportion. The method is the first method for achieving segmentation of multiple core components in the ultrasound cardiogram of the fetus with multiple diseases, greatly assists doctors in statistical analysis of multiple key indexes of the heart of the fetus, and is beneficial to remote medical treatment, especially to improvement of the medical level of grassroots remote areas.

Description

technical field [0001] The invention relates to a multi-component semantic segmentation method based on a multi-disease fetal four-chamber view. Background technique [0002] In clinical practice, ultrasonography is an important part of prenatal examination, which can provide reliable and clear information, provide scientific consultation services for pregnant women, and give appropriate postpartum guidance strategies. [0003] However, at present, more studies are based on adult echocardiography, and research on the left atrial LV; although some studies have shown that the segmentation of the adult LV and the segmentation based on the four-chamber view have been used. Left atrium LV segmentation is performed on the four-chamber images of end-systolic ES and end-diastole ED; however, there is still no solution for multi-disease multi-component segmentation, and there is no multi-component segmentation method for multi-disease fetal four-chamber view. Contents of the invent...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/34G06K9/62G06N3/04G06N3/08A61B8/08
CPCG06N3/08A61B8/52A61B8/0883A61B8/0866G06V10/267G06V2201/03G06N3/045G06F18/214G06F18/25
Inventor 朱皞罡杨汀阳安山
Owner BEIHANG UNIV
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