Co-attention spatial transformer network for unsupervised motion tracking and cardiac strain analysis in 3D echocardiography
Myocardial ischemia/infarction causes wall-motion abnormalities in the left ventricle. Therefore, reliable motion estimation and strain analysis using 3D+time echocardiography for localization and characterization of myocardial injury is valuable for early detection and targeted interventions. Previ...
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Veröffentlicht in: | Medical image analysis 2023-02, Vol.84, p.102711-102711, Article 102711 |
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Zusammenfassung: | Myocardial ischemia/infarction causes wall-motion abnormalities in the left ventricle. Therefore, reliable motion estimation and strain analysis using 3D+time echocardiography for localization and characterization of myocardial injury is valuable for early detection and targeted interventions. Previous unsupervised cardiac motion tracking methods rely on heavily-weighted regularization functions to smooth out the noisy displacement fields in echocardiography. In this work, we present a Co-Attention Spatial Transformer Network (STN) for improved motion tracking and strain analysis in 3D echocardiography. Co-Attention STN aims to extract inter-frame dependent features between frames to improve the motion tracking in otherwise noisy 3D echocardiography images. We also propose a novel temporal constraint to further regularize the motion field to produce smooth and realistic cardiac displacement paths over time without prior assumptions on cardiac motion. Our experimental results on both synthetic and in vivo 3D echocardiography datasets demonstrate that our Co-Attention STN provides superior performance compared to existing methods. Strain analysis from Co-Attention STNs also correspond well with the matched SPECT perfusion maps, demonstrating the clinical utility for using 3D echocardiography for infarct localization.
•We present a novel co-attention spatial transformer network for unsupervised motion tracking of left ventricle in 3D echocardiography.•Co-attention mechanism allows better feature extraction that leads to smoother motion fields and also interpretability.•We also present a temporal regularization term to further guide the motion of the left ventricle.•3D cardiac strain analysis was done using the motion field output and compared against 99mTc-tetrofosmin SPECT perfusion/viability maps.•Our 3D echo-derived strain maps allow reliable method to localize/quantify regional changes in myocardial strain after ischemic injury. |
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ISSN: | 1361-8415 1361-8423 |
DOI: | 10.1016/j.media.2022.102711 |