Evidence map›Paper›PMID 25574428›Full record

ArticleBiomedical optics express2014

Automated method for the segmentation and morphometry of nerve fibers in large-scale CARS images of spinal cord tissue.

Steve Bégin, Olivier Dupont-Therrien, Erik Bélanger, Amy Daradich, Sophie Laffray, Yves De Koninck, Daniel C Côté

Open access · goldAbstract read
In one paragraph

Article in Biomedical optics express, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.4field-weighted citation impact, top 5% 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

19 citing papers in PubMed, 43 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Steve BéginCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Département de physique, génie physique et optique, Université Laval, Québec, Canada ; Centre d'optique, photonique et laser (COPL), Université Laval, Québec, Canada.
Olivier Dupont-TherrienCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Centre d'optique, photonique et laser (COPL), Université Laval, Québec, Canada.
Erik BélangerCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Département de physique, génie physique et optique, Université Laval, Québec, Canada ; Centre d'optique, photonique et laser (COPL), Université Laval, Québec, Canada.
Amy DaradichCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Département de physique, génie physique et optique, Université Laval, Québec, Canada ; Centre d'optique, photonique et laser (COPL), Université Laval, Québec, Canada.
Sophie LaffrayCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Centre d'optique, photonique et laser (COPL), Université Laval, Québec, Canada.
Yves De KoninckCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Département de psychiatrie et de neurosciences, Université Laval, Québec, Canada.
Daniel C CôtéCentre de recherche de l'Institut universitaire en santé mentale de Québec (CRIUSMQ), Université Laval, Québec, Canada ; Département de physique, génie physique et optique, Université Laval, Québec, Canada ; Centre d'optique, photonique et laser (COPL), Université Laval, Québec, Canada.
Université Laval · CAInstitut Universitaire en Santé Mentale de Québec · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fully automated method for large-scale segmentation of nerve fibers from coherent anti-Stokes Raman scattering (CARS) microscopy images is presented. The method is specifically designed for CARS images of transverse cross sections of nervous tissue but is also suitable for use with standard light microscopy images. After a detailed description of the two-part segmentation algorithm, its accuracy is quantified by comparing the resulting binary images to manually segmented images. We then demonstrate the ability of our method to retrieve morphological data from CARS images of nerve tissue. Finally, we present the segmentation of a large mosaic of CARS images covering more than half the area of a mouse spinal cord cross section and show evidence of clusters of neurons with similar g-ratios throughout the spinal cord.

Indexed as

(000.1430) Biology and medicine(100.2960) Image analysis(170.3880) Medical and biological imaging(170.4580) Optical diagnostics for medicine(180.4315) Nonlinear microscopy(180.6900) Three-dimensional microscopy(300.6230) Spectroscopy, coherent anti-Stokes Raman scattering

Identifiers

PMID25574428
PMCPMC4285595
OpenAlexW2017966457

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.