Evidence map›Paper›PMID 34261057›Full record

ArticlePhysics in medicine and biology2021

A geometry-guided deep learning technique for CBCT reconstruction.

Ke Lu, Lei Ren, Fang-Fang Yin

Abstract readLetter
In one paragraph

Article in Physics in medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. [Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Review
  4. Article
  5. Review
  6. 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.

Ke LuMedical Physics Graduate Program, Duke University, Durham, NC, United States of America.ORCID 0000-0001-8513-3352
Lei RenMedical Physics Graduate Program, Duke University, Durham, NC, United States of America.
Fang-Fang YinMedical Physics Graduate Program, Duke University, Durham, NC, United States of America.

Funding

Hybrid virtual-MRI/CBCT: A new paradigm for image guidance in liver SBRTR01EB028324 · NIBIB · UNIVERSITY OF MARYLAND BALTIMORE · PI REN, LEI, YIN, FANG-FANG · 2019 to 2022
$2.1M
A Limited-angle Intra-fractional Verification (LIVE) System for SBRT TreatmentsR01CA184173 · NCI · DUKE UNIVERSITY · PI REN, LEI, YIN, FANG-FANG · 2015 to 2018
$1.5M
NCI NIH HHS R01 CA184173NIBIB NIH HHS R01 EB028324
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Deep LearningSpiral Cone-Beam Computed TomographyAlgorithmsCone-Beam Computed TomographyFour-Dimensional Computed TomographyImage Processing, Computer-AssistedPhantoms, ImagingCBCTdeep learningfully connected layerreconstruction

Identifiers

PMID34261057
PMCPMC9019576

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.