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Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography

机译：多视图微晶配准：在3D超声心动图估计运动和应变中的应用

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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.
机译：本文提出了一种新的注册框架，用于从多个3D超声（US）序列的组合中量化心肌运动和应变。我们方法的独创性在于直接从输入的多个视图而不是从单个视图或重构的复合序列估计变换。这使我们能够利用输入视图中所有可用的时空信息，避免可能导致运动量化结果不一致的遮挡和图像融合错误。我们提出了一种多视图微分配准策略，该策略通过对时空域进行建模来增强平滑度和一致性4D速度场在空间和时间上连续不断。这种4D连续表示将3D US序列作为一个整体来考虑，因此可以稳健地应对心率的变化，从而导致每个心动周期针对不同视图获取的图像数量不同。这有助于通过解决所有输入序列的单个转换而获得的鲁棒性。相似性度量标准考虑了美国图像的物理特性，并使用加权方案来平衡不同视图的影响。它包括连续图像之间以及参考图像和以下每个图像之间的比较。使用重建位移场的空间导数在本地计算应变张量，并在已知地面真理的合成3D US序列上评估配准和应变精度。还对8位志愿者和1位接受心脏再同步治疗的患者的多视图3D数据集进行了实验。从我们的多视图方法获得的应变曲线与单视图情况以及其他多视图方法进行了比较。对于健康病例，纳入多个视图可改善应变曲线的一致性，并减少观察到非生理性应变模式的节段数。对于患者而言，区域应变同步性的改善（起搏开或关）与临床医生的盲目评估有关，使用多视图方法可以更清楚地看到。

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