Evidence map›Paper›PMID 33552869›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2021

Deep Learning Enables Superior Photoacoustic Imaging at Ultralow Laser Dosages.

Huangxuan Zhao, Ziwen Ke, Fan Yang, Ke Li, Ningbo Chen, Liang Song, Chuansheng Zheng, Dong Liang, Chengbo Liu

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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  12. TowardsFundamental research · 2024
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  19. Super-Low-Dose Functional and Molecular Photoacoustic Microscopy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
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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

9 authors.

Huangxuan ZhaoResearch Laboratory for Biomedical Optics and Molecular Imaging CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.ORCID https://orcid.org/0000-0002-9995-7528
Ziwen KeResearch Center for Medical AI CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.ORCID https://orcid.org/0000-0003-3298-8220
Fan YangDepartment of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan 430022 China.
Ke LiResearch Laboratory for Biomedical Optics and Molecular Imaging CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.
Ningbo ChenResearch Laboratory for Biomedical Optics and Molecular Imaging CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.
Liang SongResearch Laboratory for Biomedical Optics and Molecular Imaging CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.
Chuansheng ZhengDepartment of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan 430022 China.
Dong LiangResearch Center for Medical AI CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.
Chengbo LiuResearch Laboratory for Biomedical Optics and Molecular Imaging CAS Key Laboratory of Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China.ORCID https://orcid.org/0000-0001-7565-2044

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical-resolution photoacoustic microscopy (OR-PAM) is an excellent modality for in vivo biomedical imaging as it noninvasively provides high-resolution morphologic and functional information without the need for exogenous contrast agents. However, the high excitation laser dosage, limited imaging speed, and imperfect image quality still hinder the use of OR-PAM in clinical applications. The laser dosage, imaging speed, and image quality are mutually restrained by each other, and thus far, no methods have been proposed to resolve this challenge. Here, a deep learning method called the multitask residual dense network is proposed to overcome this challenge. This method utilizes an innovative strategy of integrating multisupervised learning, dual-channel sample collection, and a reasonable weight distribution. The proposed deep learning method is combined with an application-targeted modified OR-PAM system. Superior images under ultralow laser dosage (32-fold reduced dosage) are obtained for the first time in this study. Using this new technique, a high-quality, high-speed OR-PAM system that meets clinical requirements is now conceivable.

Indexed as

deep learningmultitask residual dense networksoptical‐resolution photoacoustic microscopyultralow laser dosage

Identifiers

PMID33552869
PMCPMC7856900

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.