In this paper, we propose an enhanced 3D myocardial strain estimation procedure, which combines complementary displacement information from multiple orientations of a single imaging modality (untagged CMR SSFP images). To estimate myocardial strain across the left ventricle, we register the sets of short-axis, four-chamber and two-chamber views via a 2D non-rigid registration algorithm implemented in a commercial software (Segment, Medviso). We then create a series of interpolating functions for the three orthogonal directions of motion and use them to deform a tetrahedral mesh representation of a patient-specific left ventricle. Additionally, we correct for overestimation of displacement by introducing a weighting scheme that is based on displacement along the long axis. The procedure was evaluated on the STACOM 2011 dataset containing CMR SSFP images for 16 healthy volunteers. We show increased accuracy in estimating the three strain components (radial, circumferential, longitudinal) compared to reported results in the challenge, for the imaging modality of interest (SSFP). Our peak strain estimates are also significantly closer to reported measurements from studies of a larger cohort in the literature and our own ground truth measurements using Segment Strain Analysis Module. Our proposed procedure provides a relatively fast and simple method to improve 2D tracking results, with the added flexibility in either deforming a reconstructed mesh model from other image modalities or using the built-in CMR mesh reconstruction procedure. Our, proposed scheme presents a deforming patient-specific model of the left ventricle, using the commonest imaging modality , routinely administered in clinical settings, without requiring additional or specialized imaging protocols.
翻译:在本文中,我们提出一个强化的3D心肌梗塞估计程序,该程序将单一成像模式(未加标记的CMR SSFP图像)多重方向的辅助性偏移信息组合起来。为了估计左侧心血管偏移,我们通过在商业软件(Sepment, Medviso)中实施的2D非硬化登记算法(Sepment, Medviso)登记了一套短轴、4张相和2张相交的心肌压力估计程序。然后,我们为3个或方形运动方向创建了一系列互插功能,并用它们来改变一个四面形网状的组合网状网状结构。此外,我们通过采用基于长轴的偏移的权重计划来纠正对流离失所的过度估计。我们在STACOM2011年的数据集中用CMRSSFP图像为16名健康志愿者进行了评估。 我们的左侧结构模型(辐射、环绕、长度)与所报告的挑战的结果相比更加准确,对于成型模型(SSFP)而言,我们最深层的测测算方法使用较接近于我们的拟议的Stalial Rest Risal 程序。