Evidence map›Paper›PMID 32637260›Full record

ArticleBiomedical optics express2020

Deep learning improves contrast in low-fluence photoacoustic imaging.

Ali Hariri, Kamran Alipour, Yash Mantri, Jurgen P Schulze, Jesse V Jokerst

Abstract read
In one paragraph

Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

48 citing papers in PubMed.

  1. Article
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  7. Review of Deep Learning Approaches for Interleaved Photoacoustic and Ultrasound (PAUS) Imaging.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2023
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  13. Review
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  20. Photoacoustic Enhancement of Ferricyanide-Treated Silver Chalcogenide-Coated Gold Nanorods.The journal of physical chemistry. C, Nanomaterials and interfaces · 2022
    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.

Ali HaririDepartment of NanoEngineering, University of California, San Diego, La Jolla, CA 92093, USA.
Kamran AlipourDepartment of Computer Science, University of California, San Diego, La Jolla, CA 92093, USA.
Yash MantriDepartment of BioEngineering, University of California, San Diego, La Jolla, CA 92093, USA.
Jurgen P SchulzeDepartment of Computer Science, University of California, San Diego, La Jolla, CA 92093, USA.
Jesse V JokerstDepartment of NanoEngineering, University of California, San Diego, La Jolla, CA 92093, USA.

Funding

Therapeutic Drug Monitoring with a Wearable Ultrasound-based SensorDP2HL137187 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JOKERST, JESSE VINCENT · 2016 to 2019
$2.7M
Vevo LAZR Photoacoustic Imaging SystemS10OD021821 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HALL, DAVID J · 2016 to 2016
$594k
Non-Invasive Detection and Staging of Decubitus and Diabetic UlcersR21AG065776 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JOKERST, JESSE VINCENT · 2020 to 2021
$575k
A Miniaturized Tool for Ultrasound Quantification of Periodontal DiseaseR21DE029025 · NIDCR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JOKERST, JESSE VINCENT · 2019 to 2020
$409k
NHLBI NIH HHS DP2 HL137187NIA NIH HHS R21 AG065776NIDCR NIH HHS R21 DE029025
6 · The paper itself

Abstract

Low fluence illumination sources can facilitate clinical transition of photoacoustic imaging because they are rugged, portable, affordable, and safe. However, these sources also decrease image quality due to their low fluence. Here, we propose a denoising method using a multi-level wavelet-convolutional neural network to map low fluence illumination source images to its corresponding high fluence excitation map. Quantitative and qualitative results show a significant potential to remove the background noise and preserve the structures of target. Substantial improvements up to 2.20, 2.25, and 4.3-fold for PSNR, SSIM, and CNR metrics were observed, respectively. We also observed enhanced contrast (up to 1.76-fold) in an in vivo application using our proposed methods. We suggest that this tool can improve the value of such sources in photoacoustic imaging.

Identifiers

PMID32637260
PMCPMC7316023

What OpenQuestion holds

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Registered trials

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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.