Spatio-temporal registration of multi-perspective 3D echocardiography for improved strain estimation

For heart diagnostics, ultrasound is generally the modality of choice due to its high temporal and spatial resolution, availability, and patient safety. Although 3D echocardiography captures the complex shape and motion of the heart with more precision than 2D, it suffers to a greater extent from poor resolution, noise, and limited field-of-view. Multi-perspective echocardiography has proven to significantly enhance both image quality and field-of-view. The greatest improvements occur when combining acquisitions from widely differing insonification angles, but this process is challenging because of substantial local structural and brightness variations and ultrasound's anisotropic nature. To handle these inconsistencies, a novel temporal and spatial registration algorithm designed is proposed. Temporal registration is achieved using low-frequency cardiac wall features and motion extracted via singular value decomposition of a spatio-temporal Casorati matrix, while spatial registration is performed using phase-only correlation of low-frequency data. The acquisitions are seamlessly fused using a 3D, oriented, wavelet transform including a near-field clutter algorithm. In vitro and in vivo testing highlights the benefits of this approach. Temporal alignment, validated against electrocardiograms, is precise, with an average error of just 2 ± 10 ms. Furthermore, our method outperforms a six-degree-of-freedom encoder-based probe tracker, reducing spatial registration error to 5 ± 3 mm from 19 ± 10 mm. The resulting longitudinal and radial strain measurements closely align with those obtained by tagged magnetic resonance imaging, demonstrating the accuracy and feasibility of this technique.

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Publication Details

Journal
Medical Image Analysis
Published
2025-09-02
DOI
https://doi.org/10.1016/j.media.2025.103791
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatio-temporal registration of multi-perspective 3D echocardiography for improved strain estimation

Patrick Houthuizen, Sjoerd Bouwmeester, Michael Sjoerdsma, F. van Heesch et al.
Medical Image Analysis
Advanced MRI Techniques and Applications
article

Spatio-temporal registration of multi-perspective 3D echocardiography for improved strain estimation

Patrick Houthuizen, Sjoerd Bouwmeester, Michael Sjoerdsma, F. van Heesch, Richard G. P. Lopata
article en

Abstract

For heart diagnostics, ultrasound is generally the modality of choice due to its high temporal and spatial resolution, availability, and patient safety. Although 3D echocardiography captures the complex shape and motion of the heart with more precision than 2D, it suffers to a greater extent from poor resolution, noise, and limited field-of-view. Multi-perspective echocardiography has proven to significantly enhance both image quality and field-of-view. The greatest improvements occur when combining acquisitions from widely differing insonification angles, but this process is challenging because of substantial local structural and brightness variations and ultrasound's anisotropic nature. To handle these inconsistencies, a novel temporal and spatial registration algorithm designed is proposed. Temporal registration is achieved using low-frequency cardiac wall features and motion extracted via singular value decomposition of a spatio-temporal Casorati matrix, while spatial registration is performed using phase-only correlation of low-frequency data. The acquisitions are seamlessly fused using a 3D, oriented, wavelet transform including a near-field clutter algorithm. In vitro and in vivo testing highlights the benefits of this approach. Temporal alignment, validated against electrocardiograms, is precise, with an average error of just 2 ± 10 ms. Furthermore, our method outperforms a six-degree-of-freedom encoder-based probe tracker, reducing spatial registration error to 5 ± 3 mm from 19 ± 10 mm. The resulting longitudinal and radial strain measurements closely align with those obtained by tagged magnetic resonance imaging, demonstrating the accuracy and feasibility of this technique.

Medical Image AnalysisVol. 107(Pt A)
NXP (Netherlands) (NL), Philips (Finland) (FI), Radboud University Nijmegen (NL), Catharina Ziekenhuis (NL), Eindhoven University of Technology (NL)
European Commission, Horizon 2020 Framework Programme, European Research Council
Openalex Percentile: Top 68%
Advanced MRI Techniques and Applications
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