Evidence map›Paper›PMID 33791553›Full record

ArticleIntegrative organismal biology (Oxford, England)2020

The Natural Historian's Guide to the CT Galaxy: Step-by-Step Instructions for Preparing and Analyzing Computed Tomographic (CT) Data Using Cross-Platform, Open Access Software.

T J Buser, O F Boyd, Á Cortés, C M Donatelli, M A Kolmann, J L Luparell, J A Pfeiffenberger, B L Sidlauskas, A P Summers

Abstract read
In one paragraph

Article in Integrative organismal biology (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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  5. Squamate ventricular cardiomyocytes: Ploidy, proliferation, and heart muscle cell size in the leopard gecko (Eublepharis macularius).Developmental dynamics : an official publication of the American Association of Anatomists · 2025
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  14. Integrative organismal biology (Oxford, England) · 2024
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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.

T J BuserDepartment of Fisheries and Wildlife, Oregon State University, Corvallis, OR, USA.ORCID 0000-0002-2518-1835
O F BoydDepartment of Integrative Biology, Oregon State University, Corvallis, OR, USA.
Á CortésDepartment of Fisheries and Wildlife, Oregon State University, Corvallis, OR, USA.
C M DonatelliDepartment of Biology, University of Ottawa, Ottawa, ON, USA.
M A KolmannDepartment of Biological Sciences, George Washington University, Washington, DC, USA.
J L LuparellDepartment of Fisheries and Wildlife, Oregon State University, Corvallis, OR, USA.
J A PfeiffenbergerDepartment of Biology, Temple University, Philadelphia, PA, USA.
B L SidlauskasDepartment of Fisheries and Wildlife, Oregon State University, Corvallis, OR, USA.
A P SummersDepartment of Biology and SAFS, University of Washington, Friday Harbor Laboratories, Friday Harbor, Washington, DC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The decreasing cost of acquiring computed tomographic (CT) data has fueled a global effort to digitize the anatomy of museum specimens. This effort has produced a wealth of open access digital three-dimensional (3D) models of anatomy available to anyone with access to the Internet. The potential applications of these data are broad, ranging from 3D printing for purely educational purposes to the development of highly advanced biomechanical models of anatomical structures. However, while virtually anyone can access these digital data, relatively few have the training to easily derive a desirable product (e.g., a 3D visualization of an anatomical structure) from them. Here, we present a workflow based on free, open source, cross-platform software for processing CT data. We provide step-by-step instructions that start with acquiring CT data from a new reconstruction or an open access repository, and progress through visualizing, measuring, landmarking, and constructing digital 3D models of anatomical structures. We also include instructions for digital dissection, data reduction, and exporting data for use in downstream applications such as 3D printing. Finally, we provide Supplementary Videos and workflows that demonstrate how the workflow facilitates five specific applications: measuring functional traits associated with feeding, digitally isolating anatomical structures, isolating regions of interest using semi-automated segmentation, collecting data with simple visual tools, and reducing file size and converting file type of a 3D model.

Identifiers

PMID33791553
PMCPMC7671151

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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.