Three-dimensional reconstruction of cardiac flows based on multi-planar velocity fields

Falahatpisheh, Ahmad; Pedrizzetti, Gianni; Kheradvar, Arash

doi:10.1007/s00348-014-1848-8

Cited by 21 publications

(19 citation statements)

References 34 publications

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“…7). 17,26,[45][46][47]64,66,68,76,77,88,91,97,98,103,130,138 However, PIV methods were mainly two dimensional until Bru¨cker introduced Stereo-PIV based on the use of two digital cameras and PIV algorithms to study the flow past artificial heart valves. 21 The testing requirements for performing stereo-PIV for characterizing the flow through mechanical heart valves has been well described by Morbiducci et al 115 Another breakthrough in PIV was the development of defocusing digital particle image velocimetry (D-DPIV).…”

Section: Particle Image Velocimetry Of Heart Valvesmentioning

confidence: 99%

“…6 More recently, multiplanar PIV (MPPIV) has been introduced to measure the flow in three dimensions. 46 This method uses two-dimensional, two-component velocity fields acquired on multiple perpendicular planes and reconstruct them into a 3D velocity field through Kriging interpolation and imposing the incompressibility constraint. 46 …”

Section: Particle Image Velocimetry Of Heart Valvesmentioning

confidence: 99%

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Emerging Trends in Heart Valve Engineering: Part IV. Computational Modeling and Experimental Studies

et al. 2015

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Abstract-In this final portion of an extensive review of heart valve engineering, we focus on the computational methods and experimental studies related to heart valves. The discussion begins with a thorough review of computational modeling and the governing equations of fluid and structural interaction. We then move onto multiscale and disease specific modeling. Finally, advanced methods related to in vitro testing of the heart valves are reviewed. This section of the review series is intended to illustrate application of computational methods and experimental studies and their interrelation for studying heart valves.

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Section: Particle Image Velocimetry Of Heart Valvesmentioning

confidence: 99%

Section: Particle Image Velocimetry Of Heart Valvesmentioning

confidence: 99%

Emerging Trends in Heart Valve Engineering: Part IV. Computational Modeling and Experimental Studies

et al. 2015

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“…Progress has been made to incorporate quantitative fluid dynamics into echocardiography using particle tracking algorithms [2,3,39] that are based mostly on the well-known optical imaging techniques of particle image velocimetry (PIV) [4][5][6] or color Doppler imaging [7][8][9][10]. Recent advances in understanding left ventricular (LV) fluid dynamics based on experimental methods [11][12][13][14] and numerical simulations [15][16][17] have shed light on many aspects of ventricular flow, such as the development of intraventricular vortices.…”

mentioning

confidence: 99%

“…Furthermore, limited frame rate of echocardiographic acquisitions-particularly in 3D-is currently a major obstacle for accurate assessment of high-velocity values and advancement of 3D ultrasound-based velocimetry modalities for intracardiac flow [21,33,37]. More recent efforts may overcome these limitations and pave the way for routine clinical applications [33,[37][38][39].…”

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confidence: 99%

On the accuracy of intracardiac flow velocimetry methods

Kheradvar

2017

J Echocardiogr

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“…Some of the noteworthy three-dimensional PIV techniques are Defocusing PIV (DDPIV) [2], Holographic PIV [3], Multi-Planar PIV [4], and Tomographic PIV [5]. The accuracy of the measurement for each 3D PIV method depends on many experimental parameters, particularly on particle image density, volume depth, and type and number of acquisition devices, which make quantitative validation challenging [6,7].…”

Section: Introductionmentioning

confidence: 99%

A framework for synthetic validation of 3D echocardiographic particle image velocimetry

Falahatpisheh

Kheradvar

2015

Meccanica

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Particle image velocimetry (PIV) has been significantly advanced since its conception in early 1990s. With the advancement of imaging modalities, applications of 2D PIV have far expanded into biology and medicine. One example is echocardiographic particle image velocimetry that is used for in vivo mapping of the flow inside the heart chambers with opaque boundaries. Velocimetry methods can help better understanding the biomechanical problems. The current trend is to develop three-dimensional velocimetry techniques that take advantage of modern medical imaging tools. This study provides a novel framework for validation of velocimetry methods that are inherently three dimensional such as but not limited to those acquired by 3D echocardiography machines. This framework creates 3D synthetic fields based on a known 3D velocity field V and a given 3D brightness field B. The method begins with computing the inverse flow V Ã based on the velocity field V. Then the transformation of B, imposed by V, is calculated using the computed inverse flow according toÞ , where x is the coordinates of voxels in B Ã , with a 3D weighted average interpolation, which provides high accuracy, low memory requirement, and low computational time. To check the validity of the framework, we generate pairs of 3D brightness fields by employing Hill's spherical vortex velocity field. B and the generated B Ã are then processed by our inhouse 3D particle image velocimetry software to obtain the interrelated velocity field. The results indicates that the computed and imposed velocity fields are in agreement.

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Three-dimensional reconstruction of cardiac flows based on multi-planar velocity fields

Cited by 21 publications

References 34 publications

Emerging Trends in Heart Valve Engineering: Part IV. Computational Modeling and Experimental Studies

Emerging Trends in Heart Valve Engineering: Part IV. Computational Modeling and Experimental Studies

On the accuracy of intracardiac flow velocimetry methods

A framework for synthetic validation of 3D echocardiographic particle image velocimetry

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