ArticleProceedings of SPIE--the International Society for Optical Engineering2016
Robust Spatio-Temporal Registration of 4D Cardiac Ultrasound Sequences.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed.
- A Review on Registration Techniques for Cardiac Computed Tomography and Ultrasound Images.Bioengineering (Basel, Switzerland) · 2025Review
- Deformable multimodal registration for navigation in beating-heart cardiac surgery.International journal of computer assisted radiology and surgery · 2019Article
- Uncertainty-aware asynchronous scattered motion interpolation using Gaussian process regression.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2019Article
- Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.International journal of computer assisted radiology and surgery · 2018Article
- Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces.Journal of medical imaging (Bellingham, Wash.) · 2017Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Registration of multiple 3D ultrasound sectors in order to provide an extended field of view is important for the appreciation of larger anatomical structures at high spatial and temporal resolution. In this paper, we present a method for fully automatic spatio-temporal registration between two partially overlapping 3D ultrasound sequences. The temporal alignment is solved by aligning the normalized cross correlation-over-time curves of the sequences. For the spatial alignment, corresponding 3D Scale Invariant Feature Transform (SIFT) features are extracted from all frames of both sequences independently of the temporal alignment. A rigid transform is then calculated by least squares minimization in combination with random sample consensus. The method is applied to 16 echocardiographic sequences of the left and right ventricles and evaluated against manually annotated temporal events and spatial anatomical landmarks. The mean distances between manually identified landmarks in the left and right ventricles after automatic registration were (mean ± SD) 4.3 ± 1.2 mm compared to a reference error of 2.8 ± 0.6 mm with manual registration. For the temporal alignment, the absolute errors in valvular event times were 14.4 ± 11.6 ms for Aortic Valve (AV) opening, 18.6 ± 16.0 ms for AV closing, and 34.6 ± 26.4 ms for mitral valve opening, compared to a mean inter-frame time of 29 ms.
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Registered trials
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