The characterization and assembly of an efficient, cost effective focused ultrasound transducer

Michael S. Maslakowski, Sheikh J. Ilham, Timothy Hall, Thyagarajan Subramanian, Mehdi Kiani, Mohamed Almekkawy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ultrasonic imaging has been a staple of medical technology for the past 50 years. Focused ultrasound (FUS) is a rising new application of ultrasonic technologies that concentrates power at focal point(s). With the precision of the focal point, FUS offers a promise for a noninvasive yet highly conformal therapy option. This has encouraged a number of research groups to investigate its feasibility in different therapeutic applications. These applications include High Intensity Focused Ultrasound (HIFU) to coagulate cancerous tumors, Medium Intensity Focused Ultrasound (MIFU) to create a disruption in the Blood-Brain Barrier (BBB) for drug delivery or Low Intensity Focused Ultrasound (LIFU) for neuromodulation. The paper offers the procedures to assemble two cost effective options for piezoelectric FUS transducers. In addition, it characterizes their performance, the effects of bonding agents and the environments on them. This process was realized through both passive characterization of the reactants and active detection with a hydrophone.

Original languageEnglish (US)
Title of host publicationProceedings of the 2020 IEEE Dallas Circuits and Systems Conference, DCAS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728185101
DOIs
StatePublished - Nov 15 2020
Event14th IEEE Dallas Circuits and Systems Conference, DCAS 2020 - Virtual, Richardson, United States
Duration: Nov 15 2020Nov 16 2020

Publication series

NameProceedings of the 2020 IEEE Dallas Circuits and Systems Conference, DCAS 2020

Conference

Conference14th IEEE Dallas Circuits and Systems Conference, DCAS 2020
CountryUnited States
CityVirtual, Richardson
Period11/15/2011/16/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Hardware and Architecture
  • Signal Processing
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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