Evidence map›Paper›PMID 38787011›Full record

ArticleTomography (Ann Arbor, Mich.)2024

Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network.

Qi Huang, Johnathan Le, Sarang Joshi, Jason Mendes, Ganesh Adluru, Edward DiBella

Abstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2024. 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
–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

3 citing papers in PubMed.

  1. Optimization of the Sequence of Computed Tomography Angiography and Perfusion in One-Stop-Shop CT Imaging for Acute Ischemic Stroke.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Article
  2. 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

6 authors.

Qi HuangUtah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108, USA.ORCID 0000-0001-6545-2487
Johnathan LeUtah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108, USA.ORCID 0000-0003-3361-7691
Sarang JoshiDepartment of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA.
Jason MendesUtah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108, USA.
Ganesh AdluruUtah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108, USA.
Edward DiBellaUtah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT 84108, USA.ORCID 0000-0001-9196-3731

Funding

Quantitative MRI for characterizing heart failure with preserved ejection fractionR01HL135328 · NHLBI · UNIVERSITY OF UTAH · PI DIBELLA, EDWARD VR · 2017 to 2020
$2.6M
Improved cardiac T1 reactivity measures for gadolinium-free MRI assessment of ischemic heart diseaseR56HL162699 · NHLBI · UNIVERSITY OF UTAH · PI ADLURU, GANESH · 2022 to 2022
$489k
NHLBI NIH HHS R01 HL135328NHLBI NIH HHS R56 HL162699NIH HHS R56HL 162699NIH HHS RO1HL 135328
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Magnetic Resonance ImagingComputer SimulationContrast MediaCoronary CirculationHumansImage Processing, Computer-AssistedNeural Networks, ComputerContrast MediaAIF correctionAIF saturationarterial input functionBi-LSTMdeep learningmyocardial perfusion MRI

Identifiers

PMID38787011
PMCPMC11126045

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.