Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography
This paper presents a new registration framework for quantifying myocardial motion and strain from the combination of multiple 3D ultrasound (US) sequences. The originality of our approach lies in the estimation of the transformation directly from the input multiple views rather than from a single v...
| Հիմնական հեղինակներ: | , , , , , , , |
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| Ձևաչափ: | Journal article |
| Լեզու: | English |
| Հրապարակվել է: |
2013
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| _version_ | 1826276837117919232 |
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| author | Piella, G Craene, MD Butakoff, C Grau, V Yao, C Nedjati-Gilani, S Penney, G Frangi, A |
| author_facet | Piella, G Craene, MD Butakoff, C Grau, V Yao, C Nedjati-Gilani, S Penney, G Frangi, A |
| author_sort | Piella, G |
| collection | OXFORD |
| description | This paper presents a new registration framework for quantifying myocardial motion and strain from the combination of multiple 3D ultrasound (US) sequences. The originality of our approach lies in the estimation of the transformation directly from the input multiple views rather than from a single view or a reconstructed compounded sequence. This allows us to exploit all spatiotemporal information available in the input views avoiding occlusions and image fusion errors that could lead to some inconsistencies in the motion quantification result.We propose a multiview diffeomorphic registration strategy that enforces smoothness and consistency in the spatiotemporal domain by modeling the 4D velocity field continuously in space and time. This 4D continuous representation considers 3D US sequences as a whole, therefore allowing to robustly cope with variations in heart rate resulting in different number of images acquired per cardiac cycle for different views. This contributes to the robustness gained by solving for a single transformation from all input sequences. The similarity metric takes into account the physics of US images and uses a weighting scheme to balance the contribution of the different views. It includes a comparison both between consecutive images and between a reference and each of the following images. The strain tensor is computed locally using the spatial derivatives of the reconstructed displacement fields.Registration and strain accuracy were evaluated on synthetic 3D US sequences with known ground truth. Experiments were also conducted on multiview 3D datasets of 8 volunteers and 1 patient treated by cardiac resynchronization therapy. Strain curves obtained from our multiview approach were compared to the single-view case, as well as with other multiview approaches. For healthy cases, the inclusion of several views improved the consistency of the strain curves and reduced the number of segments where a non-physiological strain pattern was observed. For the patient, the improvement (pacing ON vs. OFF) in synchrony of regional strain correlated with clinician blind assessment and could be seen more clearly when using the multiview approach. © 2013 Elsevier B.V. |
| first_indexed | 2024-03-06T23:19:49Z |
| format | Journal article |
| id | oxford-uuid:685d0b2b-7e8d-4b8e-ad4e-fb42187dff15 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T23:19:49Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:685d0b2b-7e8d-4b8e-ad4e-fb42187dff152022-03-26T18:44:20ZMultiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiographyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:685d0b2b-7e8d-4b8e-ad4e-fb42187dff15EnglishSymplectic Elements at Oxford2013Piella, GCraene, MDButakoff, CGrau, VYao, CNedjati-Gilani, SPenney, GFrangi, AThis paper presents a new registration framework for quantifying myocardial motion and strain from the combination of multiple 3D ultrasound (US) sequences. The originality of our approach lies in the estimation of the transformation directly from the input multiple views rather than from a single view or a reconstructed compounded sequence. This allows us to exploit all spatiotemporal information available in the input views avoiding occlusions and image fusion errors that could lead to some inconsistencies in the motion quantification result.We propose a multiview diffeomorphic registration strategy that enforces smoothness and consistency in the spatiotemporal domain by modeling the 4D velocity field continuously in space and time. This 4D continuous representation considers 3D US sequences as a whole, therefore allowing to robustly cope with variations in heart rate resulting in different number of images acquired per cardiac cycle for different views. This contributes to the robustness gained by solving for a single transformation from all input sequences. The similarity metric takes into account the physics of US images and uses a weighting scheme to balance the contribution of the different views. It includes a comparison both between consecutive images and between a reference and each of the following images. The strain tensor is computed locally using the spatial derivatives of the reconstructed displacement fields.Registration and strain accuracy were evaluated on synthetic 3D US sequences with known ground truth. Experiments were also conducted on multiview 3D datasets of 8 volunteers and 1 patient treated by cardiac resynchronization therapy. Strain curves obtained from our multiview approach were compared to the single-view case, as well as with other multiview approaches. For healthy cases, the inclusion of several views improved the consistency of the strain curves and reduced the number of segments where a non-physiological strain pattern was observed. For the patient, the improvement (pacing ON vs. OFF) in synchrony of regional strain correlated with clinician blind assessment and could be seen more clearly when using the multiview approach. © 2013 Elsevier B.V. |
| spellingShingle | Piella, G Craene, MD Butakoff, C Grau, V Yao, C Nedjati-Gilani, S Penney, G Frangi, A Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography |
| title | Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography |
| title_full | Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography |
| title_fullStr | Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography |
| title_full_unstemmed | Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography |
| title_short | Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography |
| title_sort | multiview diffeomorphic registration application to motion and strain estimation from 3d echocardiography |
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