Evidence map›Paper›PMID 29973975›Full record

ArticleProceedings. IEEE International Symposium on Biomedical Imaging2018

4D CONTINUOUS MEDIAL REPRESENTATION BY GEODESIC SHAPE REGRESSION.

Sungmin Hong, James Fishbaugh, Guido Gerig

Abstract read
In one paragraph

Article in Proceedings. IEEE International Symposium on Biomedical Imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Diffeomorphic Medial Modeling.Information processing in medical imaging : proceedings of the ... conference · 2019
    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.

Sungmin HongComputer Science and Engineering, Tandon School of Engineering, New York University.
James FishbaughComputer Science and Engineering, Tandon School of Engineering, New York University.
Guido GerigComputer Science and Engineering, Tandon School of Engineering, New York University.

Funding

NEUROBIOLOGICAL PREDICTORS OF HUNTINGTON'S DISEASER01NS040068 · NINDS · UNIVERSITY OF IOWA · PI PAULSEN, JANE S · 2001 to 2013
$48.5M
Washington University ConsoritumU54EB005149 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI KIKINIS, RON · 2004 to 2013
$39.3M
Shape Analysis Toolbox: From medical images to quantitative insights of anatomyR01EB021391 · NIBIB · KITWARE, INC. · PI PANIAGUA, BEATRIZ · 2016 to 2024
$3.5M
Cocaine and Maternal Behavior: Effects on Trajectory of Infant Brain DevelopmentR01DA038215 · NIDA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GREWEN, KAREN M · 2016 to 2020
$3.2M
4D Shape Analysis for Modeling Spatiotemporal Change Trajectories in Huntington'sU01NS082086 · NINDS · UNIVERSITY OF UTAH · PI GERIG, GUIDO · 2012 to 2014
$1.2M
BRAINS Morphology and Image AnalysisR01NS050568 · NINDS · UNIVERSITY OF IOWA · PI MAGNOTTA, VINCENT A · 2007 to 2009
$1.0M
NIBIB NIH HHS R01 EB021391NIBIB NIH HHS U54 EB005149NIDA NIH HHS R01 DA038215NINDS NIH HHS R01 NS040068NINDS NIH HHS R01 NS050568NINDS NIH HHS U01 NS082086
6 · The paper itself

Abstract

Longitudinal shape analysis has shown great potential to model anatomical processes from baseline to follow-up observations. Shape regression estimates a continuous trajectory of time-discrete anatomical shapes to quantify temporal changes. The need for shape alignment and point-to-point correspondences represent limitations of current shape analysis methodologies, and present significant challenges in shape evaluation. We propose a method that estimates a continuous trajectory of continuous medial representations (CM-Rep) from a set of time-discrete observed shapes. To avoid the traditional step of aligning individual objects, shape changes are modeled via diffeomorphic ambient space deformations. Using a medial shape representation, we separately capture object pose changes and intrinsic geometry changes. Tests and validation with synthetic and real anatomical shapes demonstrate that the new method captures extrinsic shape changes as well as intrinsic shape changes encoded with CM-Reps, a highly relevant property for studying growth and disease processes.

Indexed as

BrainModeling - Anatomicalphysiological and pathologicalShape Analysis

Identifiers

PMID29973975
PMCPMC6027751

What OpenQuestion holds

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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.