Evidence map›Paper›PMID 31043764›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2018

Deformable model reconstruction of the subarachnoid space.

Jeffrey Glaister, Muhan Shao, Xiang Li, Aaron Carass, Snehashis Roy, Ari M Blitz, Jerry L Prince, Lotta M Ellingsen

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 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
0.2field-weighted citation impact, top 46% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  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

8 authors at 2 institutions in 2 countries.

Jeffrey GlaisterDept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD.
Muhan ShaoDept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD.
Xiang LiDept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD.
Aaron CarassDept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD.
Snehashis RoyCNRM, The Henry M. Jackson Foundation, Bethesda, MD.
Ari M BlitzDept. of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD.
Jerry L PrinceDept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD.
Lotta M EllingsenDept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD.
Johns Hopkins University · USHenry M. Jackson Foundation · US

Funding

IN VIVO MEASUREMENT OF BRAIN BIOMECHANICSR01NS055951 · NINDS · WASHINGTON UNIVERSITY · PI BAYLY, PHILIP V · 2007 to 2017
$3.9M
Ventricle segmentation and labeling to characterize normal pressure hydrocephalusR21NS096497 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PRINCE, JERRY L · 2016 to 2017
$426k
NINDS NIH HHS R01 NS055951NINDS NIH HHS R21 NS096497
6 · The paper itself

Abstract

The subarachnoid space is a layer in the meninges that surrounds the brain and is filled with trabeculae and cerebrospinal fluid. Quantifying the volume and thickness of the subarachnoid space is of interest in order to study the pathogenesis of neurodegenerative diseases and compare with healthy subjects. We present an automatic method to reconstruct the subarachnoid space with subvoxel accuracy using a nested deformable model. The method initializes the deformable model using the convex hull of the union of the outer surfaces of the cerebrum, cerebellum and brainstem. A region force is derived from the subject's Tl-weighted and T2-weighted MRI to drive the deformable model to the outer surface of the subarachnoid space. The proposed method is compared to a semi-automatic delineation from the subject's T2-weighted MRI and an existing multi-atlas-based method. A small pilot study comparing the volume and thickness measurements in a set of age-matched subjects with normal pressure hydrocephalus and healthy controls is presented to show the efficacy of the proposed method.

Indexed as

deformable modelsMRInormal pressure hydrocephalussubarachnoid space

Identifiers

PMID31043764
PMCPMC6488218
OpenAlexW2793302861

What OpenQuestion holds

Textmetadata
LicenceTDM
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.