Fhsu-Net: Deep Learning-Based Model for the Extraction of Fetal Heart Sounds in Abdominal Phonocardiography-Reference-Cited by-同舟云学术

Fhsu-Net: Deep Learning-Based Model for the Extraction of Fetal Heart Sounds in Abdominal Phonocardiography

Published:2023-09-17 Issue: Volume: Page:
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Container-title:2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)
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Author:

Alkhodari Mohanad¹,Almadani Murad¹,Ghosh Samit Kumar¹,Khandoker Ahsan H.¹

Affiliation:

1. Khalifa University,Healthcare Engineering Innovation Center (HEIC), Department of Biomedical Engineering,Abu Dhabi,UAE,127788

Funder

Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10285838/10285858/10285907.pdf?arnumber=10285907

Reference17 articles.

1. Validation of beat by beat fetal heart signals acquired from four-channel fetal phonocardiogram with fetal electrocardiogram in healthy late pregnancy;khandoker;Scientific Reports,2018

2. Fetal heart rate estimation from phonocardiograms using an emd based method;taralunga;Proceedings of the 19th International Conference on Computers Recent Advances in Computer Science (Zakynthos Island Deauville),2015

3. BioCPPNet: automatic bioacoustic source separation with deep neural networks;bermant;Scientific Reports,2021

4. Hybrid dilation and attention residual U-Net for medical image segmentation

5. Fetal Heart Sounds Detection Using Wavelet Transform and Fractal Dimension

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