Evidence map›Paper›PMID 37122476›Full record

ArticleJournal of biomedical optics2023

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

Xie Hui, Praveenbalaji Rajendran, Muhamad Ar Iskandar Zulkifli, Tong Ling, Manojit Pramanik

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xie HuiNanyang Technological University, School of Chemistry, Chemical Engineering and Biotechnology, Singapore.ORCID 0000-0001-6195-5714
Praveenbalaji RajendranStanford University, Department of Radiation Oncology, Stanford, California, United States.ORCID 0000-0001-7878-9847
Muhamad Ar Iskandar ZulkifliNanyang Technological University, School of Chemistry, Chemical Engineering and Biotechnology, Singapore.
Tong LingNanyang Technological University, School of Chemistry, Chemical Engineering and Biotechnology, Singapore.ORCID 0000-0001-9009-7966
Manojit PramanikIowa State University, Department of Electrical and Computer Engineering, Ames, Iowa, United States.ORCID 0000-0003-2865-5714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 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.

Indexed as

Cell PhoneTomography, X-Ray ComputedAlgorithmsAnimalsImage Processing, Computer-AssistedPoint-of-Care SystemsTomographyAndroid applicationapp developmentimage reconstructionmobile systemphotoacoustic tomography

Identifiers

PMID37122476
PMCPMC10133999

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.