Evidence map›Paper›PMID 38013746›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2023

Investigation of probability maps in deep-learning-based brain ventricle parcellation.

Yuli Wang, Anqi Feng, Yuan Xue, Muhan Shao, Ari M Blitz, Mark G Luciano, Aaron Carass, Jerry L Prince

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

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. AUTOMATED VENTRICLE PARCELLATION AND EVAN'S RATIO COMPUTATION IN PRE- AND POST-SURGICAL VENTRICULOMEGALY.Proceedings. IEEE International Symposium on Biomedical Imaging · 2023
    Article
  3. 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 1 country.

Yuli WangDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Anqi FengDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Yuan XueDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Muhan ShaoDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Ari M BlitzDepartment of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA.
Mark G LucianoDepartment of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Aaron CarassDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Jerry L PrinceDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Johns Hopkins University · USCase Western Reserve University · US

Funding

A Placebo-Controlled Effectiveness in INPH Shunting (PENS) TrialU01NS122764 · NINDS · JOHNS HOPKINS UNIVERSITY · PI Richard Holubkov, Mark Gregory Luciano · 2021 to 2026
$13.9M
Segmenting the subarachnoid space and dura from clinical MRIR21NS120286 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PRINCE, JERRY L · 2020 to 2020
$454k
NINDS NIH HHS R21 NS120286NINDS NIH HHS U01 NS122764
6 · The paper itself

Abstract

Normal Pressure Hydrocephalus (NPH) is a brain disorder associated with ventriculomegaly. Accurate segmentation of the ventricle system into its sub-compartments from magnetic resonance images (MRIs) could help evaluate NPH patients for surgical intervention. In this paper, we modify a 3D U-net utilizing probability maps to perform accurate ventricle parcellation, even with grossly enlarged ventricles and post-surgery shunt artifacts, from MRIs. Our method achieves a mean dice similarity coefficient (DSC) on whole ventricles for healthy controls of 0.864 ± 0.047 and 0.961 ± 0.024 for NPH patients. Furthermore, with the benefit of probability maps, the proposed method provides superior performance on MRI with grossly enlarged ventricles (mean DSC value of 0.965 ± 0.027) or post-surgery shunt artifacts (mean DSC value of 0.964 ± 0.031). Results indicate that our method provides a high robust parcellation tool on the ventricular systems which is comparable to other state-of-the-art methods.

Indexed as

MRInormal pressure hydrocephalusprobability mapventricle parcellation

Identifiers

PMID38013746
PMCPMC10679955
OpenAlexW4362604138

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.