Transport of Intensity phase imaging by intensity spectrum fitting of exponentially spaced defocus planes

Zhong, Jingshan; Claus, Rene A.; Dauwels, Justin; Tian, Lei; Waller, Laura

doi:10.1364/oe.22.010661

Cited by 140 publications

(66 citation statements)

References 30 publications

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“…A variation of this technique is proposed in [18], where wavelet shrinkage is shown to improve the accuracy over the polynomial fitting method. The authors of [19] have presented a framework in which they estimate the axial derivative of the intensity through fitting in the spatial frequency domain. Alternatively, one may combine multiple TIE solutions that are obtained by using different defocus measurements.…”

Section: A Overview Of Previous Approachesmentioning

confidence: 99%

Variational Phase Imaging Using the Transport-of-Intensity Equation

Bostan

Froustey

Nilchian

et al. 2016

IEEE Trans. on Image Process.

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Abstract-We introduce a variational phase retrieval algorithm for the imaging of transparent objects. Our formalism is based on the transport-of-intensity equation (TIE), which relates the phase of an optical field to the variation of its intensity along the direction of propagation. TIE practically requires one to record a set of defocus images to measure the variation of intensity. We first investigate the effect of the defocus distance on the retrieved phase map. Based on our analysis, we propose a weighted phase reconstruction algorithm yielding a phase map that minimizes a convex functional. The method is nonlinear and combines different ranges of spatial frequencies-depending on the defocus value of the measurements-in a regularized fashion. The minimization task is solved iteratively via the alternatingdirection method of multipliers. Our simulations outperform commonly used linear and nonlinear TIE solvers. We also illustrate and validate our method on real microscopy data of HeLa cells.

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Section: A Overview Of Previous Approachesmentioning

confidence: 99%

Variational Phase Imaging Using the Transport-of-Intensity Equation

Bostan

Froustey

Nilchian

et al. 2016

IEEE Trans. on Image Process.

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“…The measured numerical apertures (NA) of the first three circles are given in Table 2, with the two numbers for Ph1 representing the NA of the outer and inner circles. For each shape, the sample was defocused symmetrically about focus at 9 z-planes from 1µm to 16µm, exponentially spaced as in [15]. The second row of Fig.…”

Section: Resultsmentioning

confidence: 99%

“…The TIE gives a direct solution for phase as long as defocus is small. Unfortunately, images taken with small defocus have limited phase contrast, causing noise instabilities which are only partially mitigated by more z steps [12][13][14] or non-linear spacing [15].…”

Section: Introductionmentioning

confidence: 99%

Partially coherent phase imaging with simultaneous source recovery

Zhong¹,

Tian²,

Dauwels³

et al. 2014

Biomed. Opt. Express

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We propose a new method for phase retrieval that uses partially coherent illumination created by any arbitrary source shape in Köhler geometry. Using a stack of defocused intensity images, we recover not only the phase and amplitude of the sample, but also an estimate of the unknown source shape, which describes the spatial coherence of the illumination. Our algorithm uses a Kalman filtering approach which is fast, accurate and robust to noise. The method is experimentally simple and flexible, so should find use in optical, electron, X-ray and other phase imaging systems which employ partially coherent light. We provide an experimental demonstration in an optical microscope with various condenser apertures.

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“…This effect is also present in transport of intensity experiments that share similar experimental conditions (i.e. sample-camera distance < 900μm) [29,30] and other quantitative phase imaging techniques [31,32]. However, lensless phase imagers are mainly used to image biological samples like cells [4][5][6][7][8][9][10] which sizes are typically less than 20μm for which the phase can be correctly computed.…”

Section: Phase Recoverymentioning

confidence: 99%

Compact lensless phase imager

Rostykus¹,

Soulez²,

Unser³

et al. 2017

Opt. Express

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Lensless quantitative phase imaging is of high interest for obtaining a large field of view (FOV), typically the size of the camera chip, to observe biological cell material with high contrast. It has the potential to be widely spread due to its inherent simplicity. However, the tradeoff is the added complexity due to the illumination. Current illumination systems are several centimeters away from the sample, use mechanics to obtain super resolution (i.e., smaller than the detector pixel size) or different illumination directions, and block the view to the sample. In this paper, we propose and demonstrate a side illumination system which reduces the height by an order of magnitude while providing an unobstructed view of the sample. We achieve this by shaping the illumination using multiplexed analog holograms that produce 9 illumination angles. We demonstrate experimentally imaging of phase samples with a FOV of ~17mm 2 .

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Transport of Intensity phase imaging by intensity spectrum fitting of exponentially spaced defocus planes

Cited by 140 publications

References 30 publications

Variational Phase Imaging Using the Transport-of-Intensity Equation

Variational Phase Imaging Using the Transport-of-Intensity Equation

Partially coherent phase imaging with simultaneous source recovery

Compact lensless phase imager

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