Prediction and Value of Ultrasound Image in Diagnosis of Fetal Central Nervous System Malformation under Deep Learning Algorithm

Yuehong Zhou,Gustavo Ramirez

doi:10.1155/2021/6246274

Yuehong Zhou, Gustavo Ramirez

Open Access

https://doi.org/10.1155/2021/6246274

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Journal: Scientific programming	Publication Date: Jul 26, 2021
Citations: 1	License type: CC BY 4.0

Affiliation: Suizhou Central Hospital

Abstract

This study was to explore the application of deep learning neural network (DLNN) algorithms to identify and optimize the ultrasound image so as to analyze the effect and value in diagnosis of fetal central nervous system malformation (CNSM). 63 pregnant women who were gated in the hospital were suspected of being fetal CNSM and were selected as the research objects. The ultrasound images were reserved in duplicate, and one group was defined as the control group without any processing, and images in the experimental group were processed with the convolutional neural network (CNN) algorithm to identify and optimize. The ultrasound examination results and the pathological test results before, during, and after the pregnancy were observed and compared. The results showed that the test results in the experimental group were closer to the postpartum ultrasound and the results of the pathological result, but the results in both groups showed no statistical difference in contrast to the postpartum results in terms of similarity ( P > 0.05 ). In the same pregnancy stage, the ultrasound examination results of the experimental group were higher than those in the control group, and the contrast was statistically significant ( P < 0.05 ); in the different pregnancy stages, the ultrasound examination results in the second trimester were more close to the postpartum examination results, showing statistically obvious difference ( P < 0.05 ). In conclusion, ultrasonic image based on deep learning was higher in CNSM inspection; and ultrasonic technology had to be improved for the examination in different pregnancy stages, and the accuracy of the examination results is improved. However, the amount of data in this study was too small, so the representative was not high enough, which would be improved.

Highlights

With the rapid development of society, the economic level is getting better and better, the national fertility policy is relaxed, and the fertility rate of the second child increases
All pregnant women were tested using the voluson-e8 ultrasonic detector under the guidance of the same professional doctors. e continuous scanning was performed under the guidance of the Prenatal Ultrasound and Ultrasound Inspection Guide, and the specific scanning site is shown in Table 1. e ultrasound images were reserved in duplicate, and one group was defined as the control group without any processing, and images in the experimental group were processed with the convolutional neural network (CNN) algorithm to identify and optimize. e results of ultrasound examination and other clinical inspections were informed to the pregnant women, who had to decide whether to continue the pregnancy or immediately terminate the pregnancy
For pregnant women who continued to pregnancy, the fetus had to be repeatedly examined after childbirth; for pregnant women who terminated the pregnancy, the central nervous system malformation (CNSM) would be diagnosed based on the pathological results of the fetus. e diagnosis value and effect of ultrasound image based on the depth learning algorithm were analyzed by comparing the ultrasound examination results before and after the birth with the pathological test results

Summary

Introduction

With the rapid development of society, the economic level is getting better and better, the national fertility policy is relaxed, and the fertility rate of the second child increases. The number of elderly pregnant women increases with the opening of the two-child policy, leading to a higher and higher incidence of CNSM. Prenatal ultrasound examination is the most important and widely accepted method for prenatal screening of fetal CNSM [2]. It is a noninvasive examination with simple operation process, so it is a convenient and effective examination method for pregnant women. It can directly display the fetal skull structure and can conduct a better identification examination for the fetus with CNSM [3]. As the structure of the fetal nervous system is too complex and CNSM is a common type of fetal malformations, its causes are various, and the types of malformations are diverse. us, the ultrasound reflection is different, leading to a large difference in ultrasound examination in the middle of pregnancy, which is very unfavorable for the early time of the fetus [4]

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Discussion

Conclusion