Evidence map›Paper›PMID 37854548›Full record

ArticleBiomedical optics express2023

Enhancing obSTORM imaging performance with cubic spline PSF modeling.

Donghoon Koo, Minchol Lee, Youngseop Lee, Jeongmin Kim

Open access · goldAbstract read
In one paragraph

Article in Biomedical optics express, 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
1.1field-weighted citation impact, top 16% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  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

4 authors at 1 institution in 1 country.

Donghoon KooDepartment of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.ORCID https://orcid.org/0000-0002-3061-6880
Minchol LeeDepartment of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.ORCID https://orcid.org/0000-0001-5721-4809
Youngseop LeeDepartment of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.
Jeongmin KimDepartment of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.ORCID https://orcid.org/0000-0002-1235-1487
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oblique plane microscopy-based single molecule localization microscopy (obSTORM) has shown great potential for super-resolution imaging of thick biological specimens. Despite its compatibility with tissues and small animals, prior uses of the Gaussian point spread function (PSF) model have resulted in limited imaging resolution and a narrow axial localization range. This is due to the poor fit of the Gaussian PSF model with the actual PSF shapes in obSTORM. To overcome these limitations, we have employed cubic splines for a more accurate modeling of the experimental PSF shapes. This refined PSF model enhances three-dimensional localization precision, leading to significant improvements in obSTORM imaging of mouse retina tissues, such as an approximately 1.2 times increase in imaging resolution, seamless stitching of single molecules between adjacent optical sections, and a doubling of the sectional interval in volumetric obSTORM imaging due to the extended axial range of usable section thickness. The cubic spline PSF model thus offers a path towards more accurate and faster volumetric obSTORM imaging of biological specimens.

Identifiers

PMID37854548
PMCPMC10581796
OpenAlexW4386325829

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.