Evidence map›Paper›PMID 30230014›Full record

ArticleMagnetic resonance in medicine2019

Symplectomorphic registration with phase space regularization by entropy spectrum pathways.

Vitaly L Galinsky, Lawrence R Frank

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

2 authors.

Vitaly L GalinskyCenter for Scientific Computation in Imaging, University of California at San Diego, La Jolla, California.
Lawrence R FrankCenter for Scientific Computation in Imaging, University of California at San Diego, La Jolla, California.

Funding

New Quantitative Neuroimaging Metrics of Structural and Functional Connectivity of the Locus Coeruleus as a Novel Biomarker of Alzheimer's Disease Pathogenesis and ProgressionR01AG054049 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BONDI, MARK W, FRANK, LAWRENCE R · 2017 to 2021
$4.1M
Diffusion Imaging in Gray MatterR01MH096100 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FRANK, LAWRENCE R · 2012 to 2016
$1.9M
NIA NIH HHS R01 AG054049NIH HHS R01 AG054049-02NIH HHS R01 MH096100NIMH NIH HHS R01 MH096100NSF ACI-1440412NSF ACI-1550405NSF DBI-1143389NSF DBI-1147260NSF EF-0850369NSF PHY-1201238
6 · The paper itself

Abstract

purposeThe ability to register image data to a common coordinate system is a critical feature of virtually all imaging studies. However, in spite of the abundance of literature on the subject and the existence of several variants of registration algorithms, their practical utility remains problematic, as commonly acknowledged even by developers of these methods.

methodsA new registration method is presented that utilizes a Hamiltonian formalism and constructs registration as a sequence of symplectomorphic maps in conjunction with a novel phase space regularization. For validation of the framework a panel of deformations expressed in analytical form is developed that includes deformations based on known physical processes in MRI and reproduces various distortions and artifacts typically present in images collected using these different MRI modalities.

resultsThe method is demonstrated on the three different magnetic resonance imaging (MRI) modalities by mapping between high resolution anatomical (HRA) volumes, medium resolution diffusion weighted MRI (DW-MRI) and HRA volumes, and low resolution functional MRI (fMRI) and HRA volumes.

conclusionsThe method has shown an excellent performance and the panel of deformations was instrumental to quantify its repeatability and reproducibility in comparison to several available alternative approaches.

Indexed as

Diffusion Magnetic Resonance ImagingEntropyAlgorithmsArtifactsBrainComputer SimulationHumansImage Processing, Computer-AssistedModels, StatisticalNormal DistributionPhantoms, ImagingReproducibility of ResultsWorkflowdiffeomorphic mappingdiffusion tensor imagingfunctional MRInon-linear registrationsymplectomorphic mapping

Identifiers

PMID30230014
PMCPMC7098261

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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.