Method and system for imaging fetal brain channeling three-dimensional image in ultrasonic image

Abstract

The invention discloses a method for imaging fetal brain channeling three-dimensional image in an ultrasonic image, which aims to quickly and visually evaluate the development condition of fetal brainchanneling by adopting an artificial intelligence method through three-dimensional volume data of fetal brain. The method comprises the following steps: obtaining a large amount of three-dimensionalultrasonic volume data of fetal brain; inputting volume data to an intelligent imaging processing system, and manually marking brain channeling so as to obtain fetal craniocerebral three-dimensional brain channeling volume image data; inputting the fetal craniocerebral three-dimensional brain channeling volume image data into a trained 3D FCN network to obtain voxels of a fetal craniocerebral three-dimensional brain channeling volume image; automatically reconstructing a fetal craniocerebral channeling three-dimensional image by using voxels of the fetal craniocerebral three-dimensional channeling volume image, and outputting the fetal craniocerebral channeling three-dimensional image. The method can solve the technical problems that an existing clinician cannot reconstruct a fetal brain channeling three-dimensional image, the reconstruction steps are complex, the reconstruction individual difference is large, an objective analysis basis is lacked, and the result repeatability is poor.

Description

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AI Technical Summary

Benefits of technology

This technology allows us to create 3D models from an ultrasound dataset containing multiple layers of grayscale values obtained during medical procedures or examinations without having to manually adjust each layer separately. It also helps improve visualization quality when viewing these 3D model structures under realistic conditions.

Problems solved by technology

The technical problem addressed by this patented method relating to neonate cardiovascular disease (NCL) is that current noninvasive techniques cannot accurately predict or distinguish between different types of neural tissue structures associated with NCL from those seen before delivery without surgery. This results in increased patient risk due to complications caused by incorrect treatment when delivering newborns.

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