Poster Abstract: The Concept of a Lightweight Ultrasound Tomograph for Brain Scanning Using a Heterogeneous Neural Model

Grzegorz Kłosowski, Tomasz Rymarczyk, Manuchehr Soleimani

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

The primary objective of the research is the development of a lightweight and cost-effective headband-style tomographic apparatus capable of non-invasively capturing real-time internal cerebral images. A prototype of an ultrasonic tomograph was engineered, comprising a lightweight cranial band synergized with ultrasonic transducers and the tomographic system. Ultrasonic measurements were transmuted into visualizations via a heterogeneous convolutional neural network (CNN). The Ultrasonic Computed Tomography (USCT) architecture was conceived to facilitate untethered data interchange between the head-worn sensor array and the tomographic machinery.

Original languageEnglish
Title of host publicationSenSys 2023 - Proceedings of the 21st ACM Conference on Embedded Networked Sensors Systems
Place of PublicationNew York, U. S. A.
PublisherAssociation for Computing Machinery
Pages506-507
Number of pages2
ISBN (Electronic)9798400704147
DOIs
Publication statusPublished - 15 Nov 2023
Event21st ACM Conference on Embedded Networked Sensors Systems, SenSys 2023 - Istanbul, Turkey
Duration: 13 Nov 202315 Nov 2023

Publication series

NameSenSys 2023 - Proceedings of the 21st ACM Conference on Embedded Networked Sensors Systems

Conference

Conference21st ACM Conference on Embedded Networked Sensors Systems, SenSys 2023
Country/TerritoryTurkey
CityIstanbul
Period13/11/2315/11/23

Keywords

  • brain imaging
  • brain phantom
  • deep learning
  • speed of sound imaging
  • ultrasound tomography

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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