Evidence map›Paper›PMID 22493695›Full record

ArticlePloS one2012

The Digital Fish Library: using MRI to digitize, database, and document the morphological diversity of fish.

Rachel M Berquist, Kristen M Gledhill, Matthew W Peterson, Allyson H Doan, Gregory T Baxter, Kara E Yopak, Ning Kang, H J Walker, Philip A Hastings, Lawrence R Frank

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 67 citations in OpenAlex.

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  10. Morphology of the Amazonian Teleost GenusFrontiers in physiology · 2020
    Article
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  14. Open data and digital morphology.Proceedings. Biological sciences · 2017
    Review
  15. In vivo cardiovascular magnetic resonance of 2D vessel wall diffusion anisotropy in carotid arteries.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2016
    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

10 authors at 3 institutions in 1 country.

Rachel M BerquistCenter for Scientific Computation in Imaging, University of California San Diego, La Jolla, California, United States of America.
Kristen M Gledhill
Matthew W Peterson
Allyson H Doan
Gregory T Baxter
Kara E Yopak
Ning Kang
H J Walker
Philip A Hastings
Lawrence R Frank
University of California, San Diego · USUniversity of California System · USScripps Institution of Oceanography · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Museum fish collections possess a wealth of anatomical and morphological data that are essential for documenting and understanding biodiversity. Obtaining access to specimens for research, however, is not always practical and frequently conflicts with the need to maintain the physical integrity of specimens and the collection as a whole. Non-invasive three-dimensional (3D) digital imaging therefore serves a critical role in facilitating the digitization of these specimens for anatomical and morphological analysis as well as facilitating an efficient method for online storage and sharing of this imaging data. Here we describe the development of the Digital Fish Library (DFL, http://www.digitalfishlibrary.org), an online digital archive of high-resolution, high-contrast, magnetic resonance imaging (MRI) scans of the soft tissue anatomy of an array of fishes preserved in the Marine Vertebrate Collection of Scripps Institution of Oceanography. We have imaged and uploaded MRI data for over 300 marine and freshwater species, developed a data archival and retrieval system with a web-based image analysis and visualization tool, and integrated these into the public DFL website to disseminate data and associated metadata freely over the web. We show that MRI is a rapid and powerful method for accurately depicting the in-situ soft-tissue anatomy of preserved fishes in sufficient detail for large-scale comparative digital morphology. However these 3D volumetric data require a sophisticated computational and archival infrastructure in order to be broadly accessible to researchers and educators.

Indexed as

AnimalsDatabases, FactualFishesImage Processing, Computer-AssistedInternetLibraries, DigitalMagnetic Resonance Imaging

Identifiers

PMID22493695
PMCPMC3321017
OpenAlexW2058099783

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.