Ultrasound Video Segmentation of Pubic Symphysis and Fetal Head for Angle of Progression Measurement DOI

Shuangping Chen,

Huijin Wang,

Shun Long

et al.

Published: Dec. 3, 2024

Language: Английский

Artificial intelligence assisted common maternal fetal planes prediction from ultrasound images based on information fusion of customized convolutional neural networks DOI Creative Commons

Fatima Rauf,

Muhammad Attique Khan, Hussain Mobarak Albarakati

et al.

Frontiers in Medicine, Journal Year: 2024, Volume and Issue: 11

Published: Oct. 29, 2024

Ultrasound imaging is frequently employed to aid with fetal development. It benefits from being real-time, inexpensive, non-intrusive, and simple. Artificial intelligence becoming increasingly significant in medical can assist resolving many problems related the classification of organs. Processing ultrasound (US) images uses deep learning (DL) techniques. This paper aims assess development existing DL systems for use a real maternal-fetal healthcare setting. experimental process has two publicly available datasets, such as FPSU23 Dataset Fetal Imaging. Two novel architectures have been designed proposed architecture based on 3-residual 4-residual blocks different convolutional filter sizes. The hyperparameters were initialized through Bayesian Optimization. Following training process, features extracted average pooling layers both models. In subsequent step, models optimized using an improved version Generalized Normal Distribution Optimizer (GNDO). Finally, neural networks are used classify fused models, which first combined new fusion technique. best scores, 98.5 88.6% accuracy, obtained after multiple steps analysis. Additionally, comparison state-of-the-art methods revealed notable improvement suggested architecture's accuracy.

Language: Английский

Citations

6
PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images DOI
Jieyun Bai, Zihao Zhou, Zhanhong Ou

et al.

Medical Image Analysis, Journal Year: 2024, Volume and Issue: 99, P. 103353 - 103353

Published: Sept. 23, 2024

Language: Английский

Citations

4
Editorial: New technologies improve maternal and newborn safety DOI Creative Commons
Jieyun Bai,

Yaosheng Lu,

Huishu Liu

et al.

Frontiers in Medical Technology, Journal Year: 2024, Volume and Issue: 6

Published: May 30, 2024

EDITORIAL article Front. Med. Technol., 30 May 2024Sec. Medtech Data Analytics Volume 6 - 2024 | https://doi.org/10.3389/fmedt.2024.1372358

Language: Английский

Citations

3
Intrapartum Ultrasound Image Segmentation of Pubic Symphysis and Fetal Head Using Dual Student-Teacher Framework with CNN-ViT Collaborative Learning DOI

Jianmei Jiang,

Huijun Wang, Jieyun Bai

et al.

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 448 - 458

Published: Jan. 1, 2024

Language: Английский

Citations

1
A multimodal model in the prediction of the delivery mode using data from a digital twin-empowered labor monitoring system DOI Creative Commons
Jieyun Bai,

Xue Kang,

Weishan Wang

et al.

Digital Health, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 1, 2024

This study aims to address the limitations of current clinical methods in predicting delivery mode by constructing a multimodal neural network-based model. The model utilizes data from digital twin-empowered labor monitoring system, including computerized cardiotocography (cCTG), ultrasound (US) examination data, and electronic health records (EHRs) pregnant women.

Language: Английский

Citations

0
Ultrasound Video Segmentation of Pubic Symphysis and Fetal Head for Angle of Progression Measurement DOI

Shuangping Chen,

Huijin Wang,

Shun Long

et al.

Published: Dec. 3, 2024

Language: Английский

Citations

0