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

Authors:

Grzegorz Kłosowski,

Tomasz Rymarczyk,

Manuchehr SoleimaniAuthors Info & Claims

SenSys '23: Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems

Pages 506 - 507

https://doi.org/10.1145/3625687.3628380

Published: 26 April 2024 Publication History

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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.

Reference

[1]

Weibao Qiu, Ayache Bouakaz, Elisa E. Konofagou, and Hairong Zheng. 2021. Ultrasound for the Brain: A Review of Physical and Engineering Principles, and Clinical Applications. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 68, 1.

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Published In

SenSys '23: Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems

November 2023

574 pages

ISBN:9798400704147

DOI:10.1145/3625687

General Chair:
Rasit Eskicioglu,
Program Chair:
Polly Huang,
Program Co-chair:
Neal Patwari

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2024

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SenSys '23

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SenSys '23: 21st ACM Conference on Embedded Networked Sensor Systems

November 12 - 17, 2023

Istanbul, Turkiye

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Overall Acceptance Rate 174 of 867 submissions, 20%

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