Optical diffraction tomography in fluid velocimetry: the use of<i>a priori</i>information

Lobera, Julia; Coupland, John N.

doi:10.1088/0957-0233/19/7/074013

Cited by 16 publications

(16 citation statements)

References 12 publications

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“…Instead of full rotation, the illumination angle is scanned over a finite range in [202,203]. In contrast to shadow projection in other tomography methods, digital holography allows back-propagation that includes diffraction effects for more accurate and higher resolution reconstruction-also referred to as optical diffraction tomography [204,205].…”

Section: Holographic Tomographymentioning

confidence: 99%

Principles and techniques of digital holographic microscopy

2010

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Abstract. Digital holography is an emerging field of new paradigm in general imaging applications. We present a review of a subset of the research and development activities in digital holography, with emphasis on microscopy techniques and applications. First, the basic results from the general theory of holography, based on the scalar diffraction theory, are summarized, and a general description of the digital holographic microscopy process is given, including quantitative phase microscopy. Several numerical diffraction methods are described and compared, and a number of representative configurations used in digital holography are described, including off-axis Fresnel, Fourier, image plane, in-line, Gabor, and phase-shifting digital holographies. Then we survey numerical techniques that give rise to unique capabilities of digital holography, including suppression of dc and twin image terms, pixel resolution control, optical phase unwrapping, aberration compensation, and others. A survey is also given of representative application areas, including biomedical microscopy, particle field holography, micrometrology, and holographic tomography, as well as some of the special techniques, such as holography of total internal reflection, optical scanning holography, digital interference holography, and heterodyne holography. The review is intended for students and new researchers interested in developing new techniques and exploring new applications of digital holography. C 2010 Society of Photo-Optical Instrumentation Engineers.

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Section: Holographic Tomographymentioning

confidence: 99%

Principles and techniques of digital holographic microscopy

2010

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“…This is a non-linear optimization problem that would be addressed by a modified Conjugated Gradient Method (CGM) [7]. The search direction at any iteration is the negative gradient of the cost function, denoted by g(r).…”

Section: Description Of Nlodt-p Modelmentioning

confidence: 99%

“…In practice, however, multiple scattering effects are common and increase background noise, which decrease the number of velocity vectors that can be retrieved from a given flow field [4]. Tomographic methods using several recordings from different observation directions have been proposed to mitigate this problem [5,6].The application of Optical Diffraction Tomography (ODT) in HPIV, and more specifically the Non-Linear ODT, would improve the spatial resolution [7].…”

Section: Introductionmentioning

confidence: 99%

“…For the Non-Linear ODT approach [7,9], the image reconstruction is considered to be the solution that better explains the scattered far field but it requires a bigger computational cost. In the implementation of this optimization method, the Helmholtz equation needs to be solved for a known refractive index distribution and an illuminating field -the forward problem.…”

Section: Introductionmentioning

confidence: 99%

“…Both the use of a priori information concerning the object and High Performance Computing (HPC) could improve this performance. The use of a priori information can reduce instability in optimization and computational time [7,10]. In fluid velocimetry this information is on the diameter and optical properties of the seeding particles, effectively reducing the particle imaging reconstruction problem to a particle location problem, as showed in [7,11].…”

Section: Introductionmentioning

confidence: 99%

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High performance computing for a 3-D optical diffraction tomographic application in fluid velocimetry

et al. 2015

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Optical Diffraction Tomography has been recently introduced in fluid velocimetry to provide three dimensional information of seeding particle locations. In general, image reconstruction methods at visible wavelengths have to account for diffraction. Linear approximation has been used for three-dimensional image reconstruction, but a non-linear and iterative reconstruction method is required when multiple scattering is not negligible. Non-linear methods require the solution of the Helmholtz equation, computationally highly demanding due to the size of the problem. The present work shows the results of a non-linear method customized for spherical particle location using GPU computing and a made-to-measure storing format.

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Parallel resolution of the 3D Helmholtz equation based on multi‐graphics processing unit clusters

Ortega

Lobera

Garcı́a

et al. 2014

Concurrency and Computation

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SummaryThe resolution of the 3D Helmholtz equation is required in the development of models related to a wide range of scientific and technological applications. For solving this equation in complex arithmetic, the biconjugate gradient (BCG) method is one of the most relevant solvers. However, this iterative method has a high computational cost because of the large sparse matrix and the vector operations involved. In this paper, a specific BCG method, adapted for the regularities of the Helmholtz equation is presented. This BCG is based on the implementation of a novel format (named ‘Regular Format’) that allows the storage of the large sparse matrix involved in the sparse matrix vector product in a compact form. The contribution of this work is twofold: (1) decreasing the memory requirements of the 3D Helmholtz equation using the ‘Regular Format’ and (2) speeding up the resolution of the equation using high performance computing resources. A hybrid Message Passing Interface (MPI)‐graphics processing unit CUDA GPU parallelization that is capable of solving complex problems in short time has carried out (Fast‐Helmholtz). Fast‐Helmholtz combines optimizations at Message Passing Interface and GPU levels to reduce communications costs and to improve the exploitation of GPU architecture. This strategy makes it possible to extend the dimension of the Helmholtz problem to be solved, thanks to the relevant reduction of memory requirements and runtime. Copyright © 2014 John Wiley & Sons, Ltd.

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Optical diffraction tomography in fluid velocimetry: the use ofa prioriinformation

Cited by 16 publications

References 12 publications

Principles and techniques of digital holographic microscopy

Principles and techniques of digital holographic microscopy

High performance computing for a 3-D optical diffraction tomographic application in fluid velocimetry

Parallel resolution of the 3D Helmholtz equation based on multi‐graphics processing unit clusters

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