Evidence map›Paper›PMID 31803863›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2018

Hierarchical Spherical Deformation for Shape Correspondence.

Ilwoo Lyu, Martin A Styner, Bennett A Landman

Abstract read
In one paragraph

Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Ilwoo LyuElectrical Engineering and Computer Science, Vanderbilt University, TN, USA.
Martin A StynerPsychiatry, The University of North Carolina at Chapel Hill, NC, USA.
Bennett A LandmanElectrical Engineering and Computer Science, Vanderbilt University, TN, USA.

Funding

UNC MRDD Research CenterP30HD003110 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BELGER, AYSENIL · 1985 to 2012
$28.7M
Preclinical CoreU54HD079124 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MOY, SHERYL S · 2013 to 2019
$8.0M
Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRIR01EB017230 · NIBIB · VANDERBILT UNIVERSITY · PI LANDMAN, BENNETT A. · 2015 to 2024
$5.1M
RDoC Constructs: Neural Substrates, Heritability, and Relation to PsychopathologyR01MH098098 · NIMH · VANDERBILT UNIVERSITY · PI LAHEY, BENJAMIN B, ZALD, DAVID HAROLD · 2012 to 2015
$4.4M
Thalamocortical Networks in PsychosisR01MH102266 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WOODWARD, NEIL D. · 2014 to 2018
$2.3M
Developmental Brain Atlas Tools and Data Applied to Humans and MacaquesR01MH091645 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NIETHAMMER, MARC, STYNER, MARTIN ANDREAS · 2010 to 2014
$2.1M
NIBIB NIH HHS R01 EB017230NICHD NIH HHS P30 HD003110NICHD NIH HHS U54 HD079124NIMH NIH HHS R01 MH091645NIMH NIH HHS R01 MH098098NIMH NIH HHS R01 MH102266
6 · The paper itself

Abstract

We present novel spherical deformation for a landmark-free shape correspondence in a group-wise manner. In this work, we aim at both addressing template selection bias and minimizing registration distortion in a single framework. The proposed spherical deformation yields a non-rigid deformation field without referring to any particular spherical coordinate system. Specifically, we extend a rigid rotation represented by well-known Euler angles to general non-rigid local deformation via spatial-varying Euler angles. The proposed method employs spherical harmonics interpolation of the local displacements to simultaneously solve rigid and non-rigid local deformation during the optimization. This consequently leads to a continuous, smooth, and hierarchical representation of the deformation field that minimizes registration distortion. In addition, the proposed method is group-wise registration that requires no specific template to establish a shape correspondence. In the experiments, we show an improved shape correspondence with high accuracy in cortical surface parcellation as well as significantly low registration distortion in surface area and edge length compared to the existing registration methods while achieving fast registration in 3 mins per subject.

Indexed as

shape correspondencespherical harmonics interpolationspherical mappingsurface registration

Identifiers

PMID31803863
PMCPMC6892465

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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.