Spatial compression in ultrasound imaging

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

High quality three dimensional ultrasound imaging is typically attained by increasing the amount of sensors, resulting in complex hardware. Compressing measurements before sensing addresses this problem, and could enable new clinical applications. We have developed an analogue compression technique, by positioning a plastic coding mask in front of the aperture, which distorts the ultrasound field by inducing varying local echo delays. This results in a compression of the spatial ultrasound field across the sensor surface, while retaining sufficient information for 3D imaging. Using only a single sensor, complementary measurements can be obtained by rotation of the sensor and the mask to increase the conditioning of the reconstruction problem. In this work, we study a method to optimize the shape of the coding mask. To this end, we define an approximate signal model that captures the ultrasound response of the mask, and use it to pose mask shape optimization as a sensor selection problem. We solve it by relaxing it to a convex problem, as well as by using a greedy selection method. Our simulation results show that these approaches are able to outperform the random design strategy, in particular when mask rotations are included in the problem.

Original languageEnglish
Title of host publicationConference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
EditorsMichael B. Matthews
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1016-1020
Number of pages5
ISBN (Electronic)978-1-5386-1823-3
DOIs
Publication statusPublished - 2018
Event51st Asilomar Conference on Signals, Systems, and Computers, ACSSC 2017 - Pacific Grove, CA, United States
Duration: 29 Oct 20171 Nov 2017
Conference number: 51
https://signalprocessingsociety.org/blog/acssc-2018-2017-asilomar-conference-signals-systems-and-computers

Conference

Conference51st Asilomar Conference on Signals, Systems, and Computers, ACSSC 2017
Abbreviated titleACSSC
CountryUnited States
CityPacific Grove, CA
Period29/10/171/11/17
Internet address

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  • Cite this

    Van Der Meulen, P., Kruizinga, P., Bosch, J. G., & Leus, G. (2018). Spatial compression in ultrasound imaging. In M. B. Matthews (Ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 (pp. 1016-1020). [8335502] IEEE. https://doi.org/10.1109/ACSSC.2017.8335502