Android mobile-platform-based image reconstruction for photoacoustic tomography
Significance: In photoacoustic tomography (PAT), numerous reconstruction algorithms have been utilized to recover initial pressure rise distribution from the acquired pressure waves. In practice, most of these reconstructions are carried out on a desktop/workstation and the mobile-based reconstructi...
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sg-ntu-dr.10356-1694312023-07-21T15:31:52Z Android mobile-platform-based image reconstruction for photoacoustic tomography Hui, Xie Rajendran, Praveenbalaji Muhamad Ar Iskandar Zulkifli Ling, Tong Pramanik, Manojit School of Chemistry, Chemical Engineering and Biotechnology Engineering::Bioengineering Photoacoustic Tomography Image Reconstruction Significance: In photoacoustic tomography (PAT), numerous reconstruction algorithms have been utilized to recover initial pressure rise distribution from the acquired pressure waves. In practice, most of these reconstructions are carried out on a desktop/workstation and the mobile-based reconstructions are far-flung. In recent years, mobile phones are becoming so ubiquitous, and most of them encompass a higher computing ability. Hence, realizing PAT image reconstruction on a mobile platform is intrinsic, and it will enhance the adaptability of PAT systems with point-of-care applications. Aim: To implement PAT image reconstruction in Android-based mobile platforms. Approach: For implementing PAT image reconstruction in Android-based mobile platforms, we proposed an Android-based application using Python to perform beamforming process in Android phones. Results: The performance of the developed application was analyzed on different mobile platforms using both simulated and experimental datasets. The results demonstrate that the developed algorithm can accomplish the image reconstruction of in vivo small animal brain dataset in 2.4 s. Furthermore, the developed application reconstructs PAT images with comparable speed and no loss of image quality compared to that on a laptop. Employing a two-fold downsampling procedure could serve as a viable solution for reducing the time needed for beamforming while preserving image quality with minimal degradation. Conclusions: We proposed an Android-based application that achieves image reconstruction on cheap, small, and universally available phones instead of relatively bulky expensive desktop computers/laptops/workstations. A beamforming speed of 2.4 s is achieved without hampering the quality of the reconstructed image. Ministry of Education (MOE) Published version The authors would like to acknowledge the support by the Tier 1 Grant funded by the Ministry of Education in Singapore (Grant No. RG30/21). 2023-07-18T06:46:16Z 2023-07-18T06:46:16Z 2023 Journal Article Hui, X., Rajendran, P., Muhamad Ar Iskandar Zulkifli, Ling, T. & Pramanik, M. (2023). Android mobile-platform-based image reconstruction for photoacoustic tomography. Journal of Biomedical Optics, 28(4), 046009-1-046009-16. https://dx.doi.org/10.1117/1.JBO.28.4.046009 1083-3668 https://hdl.handle.net/10356/169431 10.1117/1.JBO.28.4.046009 37122476 2-s2.0-85156189626 4 28 046009-1 046009-16 en RG30/21 Journal of Biomedical Optics © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. application/pdf |
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Engineering::Bioengineering Photoacoustic Tomography Image Reconstruction Hui, Xie Rajendran, Praveenbalaji Muhamad Ar Iskandar Zulkifli Ling, Tong Pramanik, Manojit Android mobile-platform-based image reconstruction for photoacoustic tomography |
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Significance: In photoacoustic tomography (PAT), numerous reconstruction algorithms have been utilized to recover initial pressure rise distribution from the acquired pressure waves. In practice, most of these reconstructions are carried out on a desktop/workstation and the mobile-based reconstructions are far-flung. In recent years, mobile phones are becoming so ubiquitous, and most of them encompass a higher computing ability. Hence, realizing PAT image reconstruction on a mobile platform is intrinsic, and it will enhance the adaptability of PAT systems with point-of-care applications. Aim: To implement PAT image reconstruction in Android-based mobile platforms. Approach: For implementing PAT image reconstruction in Android-based mobile platforms, we proposed an Android-based application using Python to perform beamforming process in Android phones. Results: The performance of the developed application was analyzed on different mobile platforms using both simulated and experimental datasets. The results demonstrate that the developed algorithm can accomplish the image reconstruction of in vivo small animal brain dataset in 2.4 s. Furthermore, the developed application reconstructs PAT images with comparable speed and no loss of image quality compared to that on a laptop. Employing a two-fold downsampling procedure could serve as a viable solution for reducing the time needed for beamforming while preserving image quality with minimal degradation. Conclusions: We proposed an Android-based application that achieves image reconstruction on cheap, small, and universally available phones instead of relatively bulky expensive desktop computers/laptops/workstations. A beamforming speed of 2.4 s is achieved without hampering the quality of the reconstructed image. |
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School of Chemistry, Chemical Engineering and Biotechnology |
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School of Chemistry, Chemical Engineering and Biotechnology Hui, Xie Rajendran, Praveenbalaji Muhamad Ar Iskandar Zulkifli Ling, Tong Pramanik, Manojit |
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Article |
author |
Hui, Xie Rajendran, Praveenbalaji Muhamad Ar Iskandar Zulkifli Ling, Tong Pramanik, Manojit |
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Hui, Xie |
title |
Android mobile-platform-based image reconstruction for photoacoustic tomography |
title_short |
Android mobile-platform-based image reconstruction for photoacoustic tomography |
title_full |
Android mobile-platform-based image reconstruction for photoacoustic tomography |
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Android mobile-platform-based image reconstruction for photoacoustic tomography |
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Android mobile-platform-based image reconstruction for photoacoustic tomography |
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android mobile-platform-based image reconstruction for photoacoustic tomography |
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2023 |
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https://hdl.handle.net/10356/169431 |
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