Motion Correction Using Deep Learning Neural Networks - Effects of Data Representation-Reference-Cited by-同舟云学术

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Motion Correction Using Deep Learning Neural Networks - Effects of Data Representation

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Ultrasonics Symposium (IUS)
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Author:

Zaydullin Rifkat¹,Bharath Anil A.¹,Grisan Enrico²,Christensen-Jeffries Kirsten³,Bai Wenjia⁴,Tang Meng-Xing¹

Affiliation:

1. Imperial College London,Department of Bioengineering,London,United Kingdom

2. School of Engineering, London South Bank University,London,United Kingdom

3. King's College London,Department of Biomedical Engineering,London,United Kingdom

4. Imperial College London,Department of Brain Sciences & Department of Computing,London,United Kingdom

Funder

Medical Research Council

Engineering and Physical Sciences Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9957114/9957143/09958903.pdf?arnumber=9958903

Reference13 articles.

1. Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers

2. U-net: Convolutional networks for biomedical image segmentation;ronneberger;Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015,2015

3. Pytorch: An imperative style, high-performance deep learning library;paszke;Advances in neural information processing systems,2019

4. VoxelMorph: A Learning Framework for Deformable Medical Image Registration

5. Deep Learning Based Motion Tracking of Ultrasound Image Sequences

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