Evidence map›Paper›PMID 29993716›Full record

ArticleIEEE transactions on ultrasonics, ferroelectrics, and frequency control2018

GPU Accelerated Multilevel Lagrangian Carotid Strain Imaging.

Nirvedh H Meshram, Tomy Varghese

Abstract read
In one paragraph

Article in IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Mask R-CNN-based carotid plaque localization in ultrasound images.Journal of medical imaging (Bellingham, Wash.) · 2026
    Article
  3. Lagrangian deformation tracking for strain imaging.Progress in biomedical engineering (Bristol, England) · 2026
    Review
  4. Comparison of 2D and 3D carotid plaque analysis and longitudinalJournal of medical imaging (Bellingham, Wash.) · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Bayesian Regularized Strain Imaging for Assessment of Murine Cardiac Function In vivo.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021
    Article
  11. Article
  12. Spatiotemporal Bayesian Regularization for Cardiac Strain Imaging: Simulation andIEEE open journal of ultrasonics, ferroelectrics, and frequency control · 2021
    Article
  13. Article
  14. Adaptation of Dictionary Learning for Electrode Displacement ElastographyAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    Article
  15. Study of the Relationship Between Ultrasound Strain Indices and Cognitive Decline for Vulnerable Carotid Plaque.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    Article
  16. Improving Ultrasound Lateral Strain Estimation Accuracy using Log Compression of Regularized Correlation Function.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    Article
  17. Article
  18. Article
  19. Article
  20. 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

2 authors.

Nirvedh H Meshram
Tomy Varghese

Funding

Real-time Ultrasonic Monitoring of Tumor AblationR01CA112192 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI VARGHESE, TOMY · 2007 to 2017
$2.6M
Structural Stability of Carotid Plaque and SymptomatologyR01NS064034 · NINDS · UNIVERSITY OF WISCONSIN-MADISON · PI DEMPSEY, ROBERT J · 2010 to 2014
$1.5M
NCI NIH HHS R01 CA112192NINDS NIH HHS R01 NS064034
6 · The paper itself

Abstract

A multilevel Lagrangian carotid strain imaging algorithm is analyzed to identify computational bottlenecks for implementation on a graphics processing unit (GPU). Displacement tracking including regularization was found to be the most computationally expensive aspect of this strain imaging algorithm taking about 2.2 h for an entire cardiac cycle. This intensive displacement tracking was essential to obtain Lagrangian strain tensors. However, most of the computational techniques used for displacement tracking are parallelizable, and hence GPU implementation is expected to be beneficial. A new scheme for subsample displacement estimation referred to as a multilevel global peak finder was also developed since the Nelder-Mead simplex optimization technique used in the CPU implementation was not suitable for GPU implementation. GPU optimizations to minimize thread divergence and utilization of shared and texture memories were also implemented. This enables efficient use of the GPU computational hardware and memory bandwidth. Overall, an application speedup of was obtained enabling the algorithm to finish in about 50 s for a cardiac cycle. Last, comparison of GPU and CPU implementations demonstrated no significant difference in the quality of displacement vector and strain tensor estimation with the two implementations up to a 5% interframe deformation. Hence, a GPU implementation is feasible for clinical adoption and opens opportunity for other computationally intensive techniques.

Indexed as

Carotid ArteriesComputer GraphicsAlgorithmsCardiovascular Physiological PhenomenaElasticity Imaging TechniquesHumansImage Processing, Computer-AssistedPhantoms, Imaging

Identifiers

PMID29993716
PMCPMC6128663

What OpenQuestion holds

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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.