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Android mobile-platform-based image reconstruction for photoacoustic tomography.

Xie Hui1, Praveenbalaji Rajendran2, Muhamad Ar Iskandar Zulkifli1

  • 1Nanyang Technological University, School of Chemistry, Chemical Engineering and Biotechnology, Singapore.

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Summary

This study developed an Android application for photoacoustic tomography (PAT) image reconstruction on mobile phones. The application achieves fast, high-quality PAT imaging on smartphones, enhancing point-of-care applications.

Keywords:
Android applicationapp developmentimage reconstructionmobile systemphotoacoustic tomography

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Area of Science:

  • Biomedical Imaging
  • Medical Technology
  • Computational Imaging

Background:

  • Photoacoustic tomography (PAT) typically relies on desktop computers for image reconstruction, limiting its portability.
  • Advancements in mobile device computing power present an opportunity for on-device PAT image processing.
  • Current mobile-based PAT reconstruction solutions are scarce, hindering widespread adoption.

Purpose of the Study:

  • To develop and implement a PAT image reconstruction algorithm on Android-based mobile platforms.
  • To enable real-time or near-real-time PAT image reconstruction directly on smartphones.
  • To enhance the accessibility and point-of-care utility of PAT systems.

Main Methods:

  • Developed an Android application utilizing Python for the beamforming process.
  • Implemented PAT image reconstruction algorithms optimized for mobile processing.
  • Validated the application using both simulated and experimental datasets on various mobile platforms.

Main Results:

  • Achieved image reconstruction of an in vivo small animal brain dataset in 2.4 seconds.
  • Demonstrated comparable image quality and speed to traditional laptop-based reconstructions.
  • Identified a two-fold downsampling procedure as effective for reducing processing time with minimal quality loss.

Conclusions:

  • Successfully implemented PAT image reconstruction on ubiquitous Android mobile devices.
  • The developed application offers a cost-effective and portable alternative to bulky workstations.
  • Achieved rapid beamforming (2.4s) without compromising reconstructed image quality.