Evidence map›Paper›PMID 30996523›Full record

ArticleJournal of mathematical imaging and vision2018

Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D.

Erik J Bekkers, Da Chen, Jorg M Portegies

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PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of mathematical imaging and vision, 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. Computing geodesic paths encoding a curvature prior for curvilinear structure tracking.Proceedings of the National Academy of Sciences of the United States of America · 2023
    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.

Erik J Bekkers1Centre for Analysis, Scientific computing and Applications (CASA), Eindhoven University of Technology, Eindhoven, The Netherlands.
Da Chen2CNRS, UMR 7534, CEREMADE, University Paris Dauphine, PSL Research University, 75016 Paris, France.
Jorg M Portegies1Centre for Analysis, Scientific computing and Applications (CASA), Eindhoven University of Technology, Eindhoven, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose an efficient approach for the grouping of local orientations (points on vessels) via nilpotent approximations of sub-Riemannian distances in the 2D and 3D roto-translation groups SE(2) and SE(3). In our distance approximations we consider homogeneous norms on nilpotent groups that locally approximate SE(

Indexed as

Geodesic vessel trackingNilpotent approximationPerceptual groupingRoto-translation groupSE(2)SE(3)Sub-Riemannian geometry

Identifiers

PMID30996523
PMCPMC6438598

What OpenQuestion holds

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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.