Aberrator Shape Identification from 3D Ultrasound Data Using Convolutional Neural Networks and Direct Numerical Modeling-Reference-Cited by-同舟云学术

Aberrator Shape Identification from 3D Ultrasound Data Using Convolutional Neural Networks and Direct Numerical Modeling

Published:2022 Issue: Volume: Page:15-28
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Vasyukov Alexey^ORCID,Stankevich Andrey^ORCID,Beklemysheva Katerina^ORCID,Petrov Igor^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-24145-1_2

Reference20 articles.

1. Dimitris, P., Manuel, V., Florian, M., Marcel, A, Jean-Philippe, T.: Single-shot CNN-based ultrasound imaging with sparse linear arrays. In: 2020 IEEE International Ultrasonics Symposium (IUS), pp. 1–4 (2020)

2. Smart Innovation, Systems and Technologies;AS Stankevich,2021

3. Patel, D., Tibrewala, R., Vega, A., Dong, L., Hugenberg, N., Oberai, A.: Circumventing the solution of inverse problems in mechanics through deep learning: application to elasticity imaging. Comput. Methods Appl. Mech. Eng. 353, 448–466 (2019)

4. Lu, H., Wang, H., Zhang, Q., Yoon, S., Won, D.: A 3D convolutional neural network for volumetric image semantic segmentation. Procedia Manuf. 39, 422–428 (2019)

5. Potočnik, B., Šavc, M.: Deeply-supervised 3D convolutional neural networks for automated ovary and follicle detection from ultrasound volumes. Appl. Sci. 12(1246) (2022)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Model of fractured medium and nondestructive control of composite materials;Chinese Journal of Aeronautics;2024-02