Evidence map›Paper›PMID 39469302›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2024

Tagged-to-Cine MRI Sequence Synthesis via Light Spatial-Temporal Transformer.

Xiaofeng Liu, Fangxu Xing, Zhangxing Bian, Tomas Arias-Vergara, Paula Andrea Pérez-Toro, Andreas Maier, Maureen Stone, Jiachen Zhuo, Jerry L Prince, Jonghye Woo

Abstract read
In one paragraph

Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Xiaofeng LiuMassachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Fangxu XingMassachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Zhangxing BianJohns Hopkins University, Baltimore, MD, USA.
Tomas Arias-VergaraMassachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Paula Andrea Pérez-ToroMassachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Andreas MaierFriedrich-Alexander University, Erlangen, Germany.
Maureen StoneUniversity of Maryland, Baltimore, MD, USA.
Jiachen ZhuoUniversity of Maryland, Baltimore, MD, USA.
Jerry L PrinceJohns Hopkins University, Baltimore, MD, USA.
Jonghye WooMassachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

Funding

A holistic approach to identifying functional units of tongue motion during speechR01DC018511 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI WOO, JONGHYE · 2020 to 2024
$2.6M
Predictors of Speech Quality after Tongue Cancer SurgeryR01CA133015 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI STONE, MAUREEN · 2009 to 2013
$2.5M
Tongue muscle function after cancer surgery using 4D MRI, DTI, and MR taggingR01DC014717 · NIDCD · JOHNS HOPKINS UNIVERSITY · PI PRINCE, JERRY L · 2015 to 2019
$1.7M
Deep Learning for Individualized Treatment Effect Inference with Multimodal DepictionR21EB034911 · NIBIB · YALE UNIVERSITY · PI Xiaofeng Liu · 2024 to 2026
$653k
NCI NIH HHS R01 CA133015NIBIB NIH HHS R21 EB034911NIDCD NIH HHS R01 DC014717NIDCD NIH HHS R01 DC018511
6 · The paper itself

Abstract

Tagged magnetic resonance imaging (MRI) has been successfully used to track the motion of internal tissue points within moving organs. Typically, to analyze motion using tagged MRI, cine MRI data in the same coordinate system are acquired, incurring additional time and costs. Consequently, tagged-to-cine MR synthesis holds the potential to reduce the extra acquisition time and costs associated with cine MRI, without disrupting downstream motion analysis tasks. Previous approaches have processed each frame independently, thereby overlooking the fact that complementary information from occluded regions of the tag patterns could be present in neighboring frames exhibiting motion. Furthermore, the inconsistent visual appearance, e.g., tag fading, across frames can reduce synthesis performance. To address this, we propose an efficient framework for tagged-to-cine MR sequence synthesis, leveraging both spatial and temporal information with relatively limited data. Specifically, we follow a split-and-integral protocol to balance spatialtemporal modeling efficiency and consistency. The light spatial-temporal transformer (LiST

Identifiers

PMID39469302
PMCPMC11517403

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Registered trials

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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.