Evidence map›Paper›PMID 42775078›Full record

ArticleJournal of biomedical optics2026

Aberration correction and complementary beam subtraction in light-sheet fluorescence microscopy.

Yang Zhang, Ruiwen Yang, Xing Li, Dan Dan, Yanlong Yang, Yuzhu Liu, Runze Li, Jia Qian, Taiqiang Dai, Liang Kong and 2 more

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Yang ZhangChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.ORCID https://orcid.org/0009-0001-9227-4409
Ruiwen YangChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Xing LiChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Dan DanChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Yanlong YangChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Yuzhu LiuChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Runze LiChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Jia QianChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.
Taiqiang DaiThe Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Department of Oral and Maxillofacial Surgery, School of Stomatology, Xi'an, China.
Liang KongThe Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Department of Oral and Maxillofacial Surgery, School of Stomatology, Xi'an, China.
Xianghua YuChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.ORCID https://orcid.org/0000-0002-7447-1396
Baoli YaoChinese Academy of Sciences, State Key Laboratory of Ultrafast Optical Science and Technology, Xi'an Institute of Optics and Precision Mechanics, Xi'an, China.ORCID https://orcid.org/0000-0002-1723-6680

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Scanning nondiffracting Bessel beams in light-sheet fluorescence microscopy (LSFM) can expand the field of view (FOV), but side lobes of the Bessel beams produce the out-of-focus background and limit the axial resolution. Furthermore, optical aberrations degrade the image quality and affect the imaging depth. Aim: To compensate wavefront distortions and enhance the imaging performance in LSFM, we propose a method that combines the adaptive optics (AO) with the complementary beam subtraction (CBS) method in LSFM, referred as AO-CBS. Approach: In the AO-CBS method, the sensorless AO is employed to correct optical aberrations in LSFM, resulting in a notable enhancement of image contrast and signal intensity by 48%. Higher axial resolution is achieved by effectively removing the out-of-focus background through subtracting the two image stacks acquired by scanning the Bessel beam and its corresponding complementary beam. Results: The final axial resolution is improved from Conclusions: The AO-CBS method effectively addresses key issues existing in traditional Bessel beam-based LSFM, including the sidelobe-induced out-of-focus background, the limited axial resolution, and the degraded image quality caused by optical aberrations. The successful application of this idea in LSFM can serve as a design strategy to enhance the light-sheet-based imaging systems, thereby promoting the development and the application of LSFM and providing more powerful tools for biomedical imaging.

Indexed as

Image Processing, Computer-AssistedAlgorithmsAnimalsMiceMicroscopy, FluorescencePhantoms, Imagingaberration correctionadaptive opticscomplementary beam subtractionlight-sheet fluorescence microscopy

Identifiers

PMID42775078
PMCPMC13597018

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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.