Literature DB >> 25643402

A Pipeline for the Generation of Realistic 3D Synthetic Echocardiographic Sequences: Methodology and Open-Access Database.

M Alessandrini, M De Craene, O Bernard, S Giffard-Roisin, P Allain, I Waechter-Stehle, J Weese, E Saloux, H Delingette, M Sermesant, J D'hooge.   

Abstract

Quantification of cardiac deformation and strain with 3D ultrasound takes considerable research efforts. Nevertheless, a widespread use of these techniques in clinical practice is still held back due to the lack of a solid verification process to quantify and compare performance. In this context, the use of fully synthetic sequences has become an established tool for initial in silico evaluation. Nevertheless, the realism of existing simulation techniques is still too limited to represent reliable benchmarking data. Moreover, the fact that different centers typically make use of in-house developed simulation pipelines makes a fair comparison difficult. In this context, this paper introduces a novel pipeline for the generation of synthetic 3D cardiac ultrasound image sequences. State-of-the art solutions in the fields of electromechanical modeling and ultrasound simulation are combined within an original framework that exploits a real ultrasound recording to learn and simulate realistic speckle textures. The simulated images show typical artifacts that make motion tracking in ultrasound challenging. The ground-truth displacement field is available voxelwise and is fully controlled by the electromechanical model. By progressively modifying mechanical and ultrasound parameters, the sensitivity of 3D strain algorithms to pathology and image properties can be evaluated. The proposed pipeline is used to generate an initial library of 8 sequences including healthy and pathological cases, which is made freely accessible to the research community via our project web-page.

Entities:  

Year:  2015        PMID: 25643402     DOI: 10.1109/TMI.2015.2396632

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  8 in total

1.  Efficient Two-Pass 3-D Speckle Tracking for Ultrasound Imaging.

Authors:  Geng-Shi Jeng; Maria Zontak; Nripesh Parajuli; Allen Lu; Kevinminh Ta; Albert J Sinusas; James S Duncan; Matthew O'Donnell
Journal:  IEEE Access       Date:  2018-03-13       Impact factor: 3.367

2.  Unsupervised Motion Tracking of Left Ventricle in Echocardiography.

Authors:  Shawn S Ahn; Kevinminh Ta; Allen Lu; John C Stendahl; Albert J Sinusas; James S Duncan
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2020-03-16

3.  Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis.

Authors:  Nripesh Parajuli; Allen Lu; Kevinminh Ta; John Stendahl; Nabil Boutagy; Imran Alkhalil; Melissa Eberle; Geng-Shi Jeng; Maria Zontak; Matthew O'Donnell; Albert J Sinusas; James S Duncan
Journal:  Med Image Anal       Date:  2019-04-18       Impact factor: 8.545

4.  Guideline-based learning for standard plane extraction in 3-D echocardiography.

Authors:  Peifei Zhu; Zisheng Li
Journal:  J Med Imaging (Bellingham)       Date:  2018-11-20

5.  Myocardial strain imaging: review of general principles, validation, and sources of discrepancies.

Authors:  M S Amzulescu; M De Craene; H Langet; A Pasquet; D Vancraeynest; A C Pouleur; J L Vanoverschelde; B L Gerber
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2019-06-01       Impact factor: 6.875

6.  Interactive Echocardiography Translation Using Few-Shot GAN Transfer Learning.

Authors:  Long Teng; ZhongLiang Fu; Qian Ma; Yu Yao; Bing Zhang; Kai Zhu; Ping Li
Journal:  Comput Math Methods Med       Date:  2020-03-19       Impact factor: 2.238

7.  Main Uncertainties in the RF Ultrasound Scanning Simulation of the Standard Ultrasound Phantoms.

Authors:  Monika Makūnaitė; Rytis Jurkonis; Arūnas Lukoševičius; Mindaugas Baranauskas
Journal:  Sensors (Basel)       Date:  2021-06-28       Impact factor: 3.576

8.  Learning-Based Regularization for Cardiac Strain Analysis via Domain Adaptation.

Authors:  Allen Lu; Shawn S Ahn; Kevinminh Ta; Nripesh Parajuli; John C Stendahl; Zhao Liu; Nabil E Boutagy; Geng-Shi Jeng; Lawrence H Staib; Matthew O'Donnell; Albert J Sinusas; James S Duncan
Journal:  IEEE Trans Med Imaging       Date:  2021-08-31       Impact factor: 10.048

  8 in total

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