High Resolution Plane Wave Compounding Through Deep Proximal Learning

Nishith Chennakeshava; Ben Luijten; Oded Drori; Massimo Mischi; Yonina C. Eldar; Ruud J.G. van Sloun

doi:10.1109/IUS46767.2020.9251399

High Resolution Plane Wave Compounding Through Deep Proximal Learning

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

Abstract

Ultra-fast ultrasound imaging relies on coherent Plane Wave (PW) compounding to obtain sufficient spatial resolution, and contrast. However, the process of coherent PW compounding incurs a loss in temporal resolution. We propose a Deep Learning (DL) network that achieves high resolution PW compounding using a reduced number of PW transmits. We embed a model based signal processing algorithm in the design of the network, which leads to better performance through the exploitation of the prior information that is now available to the network. Our proposed method outperforms two benchmark networks, yielding approximately an 8.2% improvement in PSNR, over the next best network. Aiming for an additional boost in resolution, we moreover train towards images acquired using higher transmit frequencies.

Original language	English
Title of host publication	2020 IEEE International Ultrasonics Symposium (IUS)
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	4
ISBN (Electronic)	978-1-7281-5448-0
ISBN (Print)	978-1-7281-5449-7
DOIs	https://doi.org/10.1109/IUS46767.2020.9251399
Publication status	Published - 2020
Event	2020 IEEE International Ultrasonics Symposium, IUS 2020 - Las Vegas, United States Duration: 7 Sept 2020 → 11 Sept 2020

Conference

Conference	2020 IEEE International Ultrasonics Symposium, IUS 2020
Country/Territory	United States
City	Las Vegas
Period	7/09/20 → 11/09/20

Keywords

Machine Learning
Plane Wave Compounding
Signal Processing
Ultrasound

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10.1109/IUS46767.2020.9251399

Cite this

@inproceedings{09e776976ff64a20a2508eee16452841,

title = "High Resolution Plane Wave Compounding Through Deep Proximal Learning",

abstract = "Ultra-fast ultrasound imaging relies on coherent Plane Wave (PW) compounding to obtain sufficient spatial resolution, and contrast. However, the process of coherent PW compounding incurs a loss in temporal resolution. We propose a Deep Learning (DL) network that achieves high resolution PW compounding using a reduced number of PW transmits. We embed a model based signal processing algorithm in the design of the network, which leads to better performance through the exploitation of the prior information that is now available to the network. Our proposed method outperforms two benchmark networks, yielding approximately an 8.2\% improvement in PSNR, over the next best network. Aiming for an additional boost in resolution, we moreover train towards images acquired using higher transmit frequencies.",

keywords = "Machine Learning, Plane Wave Compounding, Signal Processing, Ultrasound",

author = "Nishith Chennakeshava and Ben Luijten and Oded Drori and Massimo Mischi and Eldar, \{Yonina C.\} and \{van Sloun\}, \{Ruud J.G.\}",

year = "2020",

doi = "10.1109/IUS46767.2020.9251399",

language = "English",

isbn = "978-1-7281-5449-7",

booktitle = "2020 IEEE International Ultrasonics Symposium (IUS)",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2020 IEEE International Ultrasonics Symposium, IUS 2020 ; Conference date: 07-09-2020 Through 11-09-2020",

}

Chennakeshava, N , Luijten, B, Drori, O, Mischi, M, Eldar, YC & van Sloun, RJG 2020, High Resolution Plane Wave Compounding Through Deep Proximal Learning. in 2020 IEEE International Ultrasonics Symposium (IUS)., 9251399, Institute of Electrical and Electronics Engineers, 2020 IEEE International Ultrasonics Symposium, IUS 2020, Las Vegas, Nevada, United States, 7/09/20. https://doi.org/10.1109/IUS46767.2020.9251399

TY - GEN

T1 - High Resolution Plane Wave Compounding Through Deep Proximal Learning

AU - Chennakeshava, Nishith

AU - Luijten, Ben

AU - Drori, Oded

AU - Mischi, Massimo

AU - Eldar, Yonina C.

AU - van Sloun, Ruud J.G.

PY - 2020

Y1 - 2020

N2 - Ultra-fast ultrasound imaging relies on coherent Plane Wave (PW) compounding to obtain sufficient spatial resolution, and contrast. However, the process of coherent PW compounding incurs a loss in temporal resolution. We propose a Deep Learning (DL) network that achieves high resolution PW compounding using a reduced number of PW transmits. We embed a model based signal processing algorithm in the design of the network, which leads to better performance through the exploitation of the prior information that is now available to the network. Our proposed method outperforms two benchmark networks, yielding approximately an 8.2% improvement in PSNR, over the next best network. Aiming for an additional boost in resolution, we moreover train towards images acquired using higher transmit frequencies.

AB - Ultra-fast ultrasound imaging relies on coherent Plane Wave (PW) compounding to obtain sufficient spatial resolution, and contrast. However, the process of coherent PW compounding incurs a loss in temporal resolution. We propose a Deep Learning (DL) network that achieves high resolution PW compounding using a reduced number of PW transmits. We embed a model based signal processing algorithm in the design of the network, which leads to better performance through the exploitation of the prior information that is now available to the network. Our proposed method outperforms two benchmark networks, yielding approximately an 8.2% improvement in PSNR, over the next best network. Aiming for an additional boost in resolution, we moreover train towards images acquired using higher transmit frequencies.

KW - Machine Learning

KW - Plane Wave Compounding

KW - Signal Processing

KW - Ultrasound

UR - https://www.scopus.com/pages/publications/85097914072

U2 - 10.1109/IUS46767.2020.9251399

DO - 10.1109/IUS46767.2020.9251399

M3 - Conference contribution

SN - 978-1-7281-5449-7

BT - 2020 IEEE International Ultrasonics Symposium (IUS)

PB - Institute of Electrical and Electronics Engineers

T2 - 2020 IEEE International Ultrasonics Symposium, IUS 2020

Y2 - 7 September 2020 through 11 September 2020

ER -

High Resolution Plane Wave Compounding Through Deep Proximal Learning

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Keywords

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