Evidence map›Paper›PMID 23028208›Full record

ArticleProceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition2010

Multi-domain, Higher Order Level Set Scheme for 3D Image Segmentation on the GPU.

Ojaswa Sharma, Qin Zhang, François Anton, Chandrajit Bajaj

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Ojaswa SharmaDTU Informatics, The Technical University of Denmark, Denmark.
Qin Zhang
François Anton
Chandrajit Bajaj

Funding

MEDICAL SCIENTIST TRAININGT32GM007308 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI PHILIPS, MARK REID · 1985 to 2019
$23.2M
Molecular and Cellular Transport in MucusR01EB000487 · NIBIB · YALE UNIVERSITY · PI IWASAKI, AKIKO, SALTZMAN, W. MARK · 2002 to 2019
$5.0M
Software Maintenance for Biomolecular ComplexesR01EB004873 · NIBIB · UNIVERSITY OF TEXAS AT AUSTIN · PI BAJAJ, CHANDRAJIT L · 2007 to 2010
$1.2M
Hierarchical Methods for Large BioMolecular ComplexesR01GM074258 · NIGMS · UNIVERSITY OF TEXAS AUSTIN · PI BAJAJ, CHANDRAJIT L · 2005 to 2010
$778k
NIBIB NIH HHS R01 EB000487NIBIB NIH HHS R01 EB004873NIGMS NIH HHS R01 GM074258NIGMS NIH HHS T32 GM007308
6 · The paper itself

Abstract

Level set method based segmentation provides an efficient tool for topological and geometrical shape handling. Conventional level set surfaces are only C(0) continuous since the level set evolution involves linear interpolation to compute derivatives. Bajaj et al. present a higher order method to evaluate level set surfaces that are C(2) continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming solver is efficient in memory usage.

Identifiers

PMID23028208
PMCPMC3461202

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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.