Evidence map›Paper›PMID 33907199›Full record

ArticleScientific reports2021

The ANTsX ecosystem for quantitative biological and medical imaging.

Nicholas J Tustison, Philip A Cook, Andrew J Holbrook, Hans J Johnson, John Muschelli, Gabriel A Devenyi, Jeffrey T Duda, Sandhitsu R Das, Nicholas C Cullen, Daniel L Gillen and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 268 papers.

0numbers the graph read from it
0cells of the map it votes in
268citing 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

268 citing papers in PubMed.

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208 more citing papers are in PubMed but not listed here.

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

14 authors.

Nicholas J TustisonDepartment of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA. ntustison@virginia.edu.
Philip A CookDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Andrew J HolbrookDepartment of Biostatistics, University of California, Los Angeles, CA, USA.
Hans J JohnsonDepartment of Electrical and Computer Engineering, University of Iowa, Philadelphia, PA, USA.
John MuschelliSchool of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Gabriel A DevenyiDepartment of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Jeffrey T DudaDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Sandhitsu R DasDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Nicholas C CullenDepartment of Clinical Sciences, Lund University, Lund, Scania, Sweden.
Daniel L GillenDepartment of Statistics, University of California, Irvine, CA, USA.
Michael A YassaDepartment of Neurobiology and Behavior, University of California, Irvine, CA, USA.
James R StoneDepartment of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA.
James C GeeDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Brian B AvantsDepartment of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA.

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Waxholm Space for Rodent NeuroinformaticsR01NS096720 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI GEE, JAMES C · 2016 to 2019
$2.4M
ITK-Lung: A Software Framework for Lung Image Processing and AnalysisR01HL133889 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GEE, JAMES C · 2017 to 2020
$2.3M
CIHRNHLBI NIH HHS R01 HL133889NIA NIH HHS U01 AG024904NINDS NIH HHS R01 NS096720
6 · The paper itself

Abstract

The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis.

Indexed as

AlgorithmsEcosystemAdultAgedBrainHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingSoftware

Identifiers

PMID33907199
PMCPMC8079440

What OpenQuestion holds

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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.