Evidence map›Paper›PMID 31300963›Full record

ArticleInternational journal of computer assisted radiology and surgery2019

Symmetry prior for epipolar consistency.

Alexander Preuhs, Andreas Maier, Michael Manhart, Markus Kowarschik, Elisabeth Hoppe, Javad Fotouhi, Nassir Navab, Mathias Unberath

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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. [A deep blur learning-based motion artifact reduction algorithm for dental cone-beam computed tomography images].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024
    Article
  3. Article
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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

8 authors at 3 institutions in 2 countries.

Alexander PreuhsPattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany. alexander.preuhs@fau.de.ORCID http://orcid.org/0000-0001-9588-2488
Andreas MaierPattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
Michael ManhartSiemens Healthcare GmbH, Forchheim, Germany.
Markus KowarschikSiemens Healthcare GmbH, Forchheim, Germany.
Elisabeth HoppePattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
Javad FotouhiDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Nassir NavabDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Mathias UnberathDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEJohns Hopkins University · USSiemens Healthineers (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFor a perfectly plane symmetric object, we can find two views-mirrored at the plane of symmetry-that will yield the exact same image of that object. In consequence, having one image of a plane symmetric object and a calibrated camera, we automatically have a second, virtual image of that object if the 3-D location of the symmetry plane is known.

methodsWe propose a method for estimating the symmetry plane from a set of projection images as the solution of a consistency maximization based on epipolar consistency. With the known symmetry plane, we can exploit symmetry to estimate in-plane motion by introducing the X-trajectory that can be acquired with a conventional short-scan trajectory by simply tilting the acquisition plane relative to the plane of symmetry.

resultsWe inspect the symmetry plane estimation on a real scan of an anthropomorphic human head phantom and show the robustness using a synthetic dataset. Further, we demonstrate the advantage of the proposed method for estimating in-plane motion using the acquired projection data.

conclusionSymmetry breakers in the human body are widely used for the detection of tumors or strokes. We provide a fast estimation of the symmetry plane, robust to outliers, by computing it directly from a set of projections. Further, by coupling the symmetry prior with epipolar consistency, we overcome inherent limitations in the estimation of in-plane motion.

Indexed as

Cone-Beam Computed TomographyPhantoms, ImagingAlgorithmsAnthropometryHeadHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMotionCone-beam CTConsistency conditionsData completenessMotion compensationSymmetryTomographic reconstruction

Identifiers

PMID31300963
OpenAlexW2962506330

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.