Designing the focal plane spacing for multifocal plane microscopy

Tahmasbi, Amir; Ram, Sripad; Chao, Jerry; Abraham, Anish V.; Tang, Felix W.; Ober, Raimund J.

doi:10.1364/oe.22.016706

Cited by 28 publications

(39 citation statements)

References 23 publications

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“…Since the total number of photons of a fluorophore is limited, the number of photons collected at each focal plane decreases with the increase of number of focal planes, which will compromise the localization accuracy. Therefore, it is important to balance the number of focal planes and their spacing toward achieving an optimum spatial resolution [27]. Figure 9(a) shows the reconstructed 3D microtubule image of a fixed HeLa cell using 1000 raw frames with our 3D MACS method.…”

Section: Performance Evaluation Of 3d Sacs and 3d Macsmentioning

confidence: 99%

3D multifocus astigmatism and compressed sensing (3D MACS) based superresolution reconstruction

Huang

Sun

Gumpper

et al. 2015

Biomed. Opt. Express

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Abstract:Single molecule based superresolution techniques (STOR-M/PALM) achieve nanometer spatial resolution by integrating the temporal information of the switching dynamics of fluorophores (emitters). When emitter density is low for each frame, they are located to the nanometer resolution. However, when the emitter density rises, causing significant overlapping, it becomes increasingly difficult to accurately locate individual emitters. This is particularly apparent in three dimensional (3D) localization because of the large effective volume of the 3D point spread function (PSF). The inability to precisely locate the emitters at a high density causes poor temporal resolution of localization-based superresolution technique and significantly limits its application in 3D live cell imaging. To address this problem, we developed a 3D high-density superresolution imaging platform that allows us to precisely locate the positions of emitters, even when they are significantly overlapped in three dimensional space. Our platform involves a multi-focus system in combination with astigmatic optics and an 1 -Homotopy optimization procedure. To reduce the intrinsic bias introduced by the discrete formulation of compressed sensing, we introduced a debiasing step followed by a 3D weighted centroid procedure, which not only increases the localization accuracy, but also increases the computation speed of image reconstruction. We implemented our algorithms on a graphic processing unit (GPU), which speeds up processing 10 times compared with central processing unit (CPU) implementation. We tested our method with both simulated data and experimental data of fluorescently labeled microtubules and were able to reconstruct a 3D microtubule image with 1000 frames (512×512) acquired within 20 seconds.

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Section: Performance Evaluation Of 3d Sacs and 3d Macsmentioning

confidence: 99%

3D multifocus astigmatism and compressed sensing (3D MACS) based superresolution reconstruction

Huang

Sun

Gumpper

et al. 2015

Biomed. Opt. Express

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show abstract

“…For a 2D localization problem, the location parameter vector is obviously reduced to θ := (x 0 , y 0 ) ∈ Θ ⊆ R 2 . The best possible accuracy with which the location of the object can be estimated, observing its pixelated image, is given by the practical localization accuracy measure (PLAM) [5][6][7]. The PLAM is determined using the Cramér-Rao lower bound (CRLB) [5,10].…”

Section: Fisher Information Matrix and Problem Formulationmentioning

confidence: 99%

“…The main diagonal elements of the inverse FIM provide lower bounds on the variance of the estimates of the unknown parameters, whereas we are interested in the estimation accuracy in terms of the standard devi-ation. Hence, the PLAM vector is defined as the element-wise square root of the main diagonal entries of the inverse FIM [6,7].…”

Section: Fisher Information Matrix and Problem Formulationmentioning

confidence: 99%

“…This is particularly important for applications such as localization-based superresolution microscopy in which the spatial resolution is closely related to the localization accuracy [2,4]. This problem has been addressed by introducing the practical localization accuracy measure (PLAM) [5][6][7]. The PLAM provides a lower bound on the accuracy with which an unknown parameter, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Determination of localization accuracy based on experimentally acquired image sets: applications to single molecule microscopy

Tahmasbi¹,

Ober²

2015

Opt. Express

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Abstract:Fluorescence microscopy is a photon-limited imaging modality that allows the study of subcellular objects and processes with high specificity. The best possible accuracy (standard deviation) with which an object of interest can be localized when imaged using a fluorescence microscope is typically calculated using the Cramér-Rao lower bound, that is, the inverse of the Fisher information. However, the current approach for the calculation of the best possible localization accuracy relies on an analytical expression for the image of the object. This can pose practical challenges since it is often difficult to find appropriate analytical models for the images of general objects. In this study, we instead develop an approach that directly uses an experimentally collected image set to calculate the best possible localization accuracy for a general subcellular object. In this approach, we fit splines, i.e. smoothly connected piecewise polynomials, to the experimentally collected image set to provide a continuous model of the object, which can then be used for the calculation of the best possible localization accuracy. Due to its practical importance, we investigate in detail the application of the proposed approach in single molecule fluorescence microscopy. In this case, the object of interest is a point source and, therefore, the acquired image set pertains to an experimental point spread function. information-theoretic analysis of single-molecule data," IEEE Signal Proc. Mag. 32(1), 58-69 (2015).

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“…TF imaging is used to acquire images of brain tissue and bone calcium in three dimensions [4, 7, 8]. High-speed TF imaging has been reported to track single-molecules in three dimensions [28], to image the entire embryos [29], and to track the 3D dynamics in live cells [5, 6, 30, 31]. Cellular network dynamics was demonstrated using TF imaging in three dimensions [7].…”

Section: Introductionmentioning

confidence: 99%

Fidelity test for through-focus or volumetric type of optical imaging methods

Attota¹

2018

Opt. Express

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Rapid increase in interest and applications of through-focus (TF) or volumetric type of optical imaging in biology and other areas has resulted in the development of several TF image collection methods. Achieving quantitative results from images requires standardization and optimization of image acquisition protocols. Several standardization protocols are available for conventional optical microscopy where a best-focus image is used, but to date, rigorous testing protocols do not exist for TF optical imaging. In this paper, we present a method to determine the fidelity of the TF optical data using the TF scanning optical microscopy images.

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Designing the focal plane spacing for multifocal plane microscopy

Cited by 28 publications

References 23 publications

3D multifocus astigmatism and compressed sensing (3D MACS) based superresolution reconstruction

3D multifocus astigmatism and compressed sensing (3D MACS) based superresolution reconstruction

Determination of localization accuracy based on experimentally acquired image sets: applications to single molecule microscopy

Fidelity test for through-focus or volumetric type of optical imaging methods

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