Speckle-based volume holographic microscopy for optically sectioned multi-plane fluorescent imaging

Hsi-Hsun Chen; Vijay Raj Singh; Yuan Luo

doi:10.1364/OE.23.007075

1. Introduction

Light induced fluorescence microscopy such as wide-field optical microscopy has been developed for a variety of biological and imaging applications. A standard wide-field fluorescence microscope offers large field of view and three-dimensional (3D) imaging information of a biological sample, but it has poor optical sectioning capabilities to reject out-of-focus background that limits its use for imaging thick tissue samples [1–3]. Many recent improvements in optical fluorescence microscopy have centered on development of optical sectioning capabilities; in particular, on increasing acquisition speed and image quality (resolution and contrast) [4,5]. In confocal scanning microscopy [4,6,7], image contrast is improved by the combination of active (focused) illumination and a pinhole placed at the conjugate of the illuminated point. The pinhole rejects background light generated from the off-focal point of the illumination. However, confocal approach requires raster scanning in two lateral dimensions as well as depth focusing.

Structured illumination microscopy [3,5,8], another form of optical sectioning modalities, aims to speed the process to obtain the wide-field image at one depth using computational reconstruction algorithms. Although it could be simpler and more cost effective than confocal microscopic techniques, it does not eliminate the scanning operation and depth focusing is still required. Ongoing efforts are focused to eliminate scanning and enhance acquisition speed for 3D imaging. The recent improvements include selective plane illumination microscopy (SPIM) [9], digital scanned light-sheet microscopy (DSLM) [10], HiLo imaging [11–13], and holographic optical sectioning (HOS) [14]. In the former systems of SPIM and DSLM, adoption of side illumination can also be thought as specialized structured illumination to excite a fluorescently labeled sample, acquiring 3D information with high speed and high contrast. A combination of side illumination and HiLo can further improve contrast [15]. HOS is a technique in which a hologram is made of a two dimensional slice of the object volume by using a coherence gating method. A hologram requires matching the path lengths of a reference and object beams to form an interference pattern. These recent advances provide significant improvement in imaging capability; nevertheless, they still require scanning along at least one axis to capture 3D information of a sample. In addition, although Fresnel incoherence correlation holography [16] replaces scanning with deconvolving the image with coherence Fresnel propagation kernel at multiple depths along the sample, it does not yield true 3D images except in the limit of a sparsely populated volume and it is not applicable for thick tissue [16,17].

Here, we experimentally demonstrate multi-plane, non-scanning optical sectioning microscopic system, which incorporates volumetric speckle illumination and multiplexed volume hologram gratings (MVHGs). The proposed speckle-based volume holographic microscopy (speckle-based VHM) has significant advantage over conventional optical imaging and holographic systems in that it does not require scanning or intensive computational reconstruction techniques to view 3D fluorescence information within a sample. In contrast to the systems in [14,16], our approach does not require stringent requirements of forming holograms during imaging, and thus speckle-based VHM does not produce twin images, which can be a serious crosstalk limitation in conventional holographic imaging [16,18]. In our approach, optically sectioned images of microscopic samples from different depths are simultaneously obtained with each plane in focus, without the need for scanning along the axial direction, as is necessary in confocal or structured illumination microscopy. Most recently, we presented the Talbot Holographic Illumination Non-scanning (THIN) fluorescence microscopy, where we utilize Talbot effect of sinusoidal structured illumination at multiple axial plane and MVHGs to image them [17]. In contrast to the THIN system, our proposed approach does not rely on periodic structure to generate Talbot patterns and thus any axial planes of interest is selected for imaging without any constraint to follow the axial location of Talbot pattern. Hence, our system greatly simplifies multi-depth optical sectioning microscopic imaging and especially its application to fluorescence holographic microscopy. The proposed system can capture multi depth-resolved fluorescence images without scanning.

In Section 2, we describe the optical setup of the speckle-based VHM, principles of MVHGs, and computational process using normal HiLo and improved HiLo with wavelet filtering for the speckle-based VHM. In Section 3, system performance is investigated using fluorescently labelled microspheres. Experimental results using tissue samples are further measured. Section 4 discusses advantages and limitations of our approach.

2. Method

The speckled-based VHM acquires pair-wise multi-plane fluorescent images, one with speckle illumination using a diffuser, and the other with standard uniform illumination by rotating the diffuser in order to statistically average the contrast of speckles [11]. A schematic diagram of the speckled-based epi-fluorescence VHM is shown in Fig. 1. A diffuser illuminated by a coherent light source will form volumetric speckle images along the axial direction. The illuminated high-contrast volumetric speckles, incident at the sample planes, are detected incoherently [18]. The speckled-based VHM system geometry is thus configured such that illuminated speckle planes occur inside the specimen, and also serve as the structured modulation for multiple axial planes imaged by MVHGs and display laterally onto the camera [19,20]. Therefore, the volumetric speckle illumination can be thought of as 3D generalization of non-uniform illumination in the transverse as well as axial directions, leading to optically sectioned VHM imaging at arbitrarily assigned multiple depths without axial scanning.

Fig. 1 (a) Schematic of the speckle-based VHM, which enables optically sectioned imaging at arbitrarily assigned multiple depths without axial scanning. (b) The angular multiplexed recording configuration of volume hologram. (c) and (d) are two-depths (named as 1 and 2) uniform images and speckle illuminated images of 25 μm beads, respectively. The separation between two planes is ~50 μm.

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2.1 Multiplexed volume holographic gratings (MVHGs) for fluorescence imaging

The MVHGs are located in the Fourier plane of the VHM system, with the setup illustrated in Fig. 1(b), using shift-angular multiplexing by sequentially recording interference patterns with two mutual coherent beams into a thick holographic material (phenanthrenquinone- doped polymethyl methacrylate, PQ-PMMA) for multi-focal fluorescent imaging [19,21]. The reference beam is a collimated wave; a point source in the signal arm is controlled and adjusted by moving lens L1 along the optical axis while lens L2 stays fixed. A different shifted Δz position is recorded for each depth, which will be imaged within the sample. It is worth mentioning that a changed nominal angle (Δθ) between two arms is necessary to avoid overlap on the CCD plane during image acquisition.

The design method of the MVHGs can be illustrated using a Bragg-matched k-sphere diagram [22] in Fig. 2. The propagation vectors of the diffracted ( ${\overset{⇀}{k}}_{d, m}$ ) and incident ( ${\overset{⇀}{k}}_{i, m}$ ) beams are given by:

\begin{matrix} {\overset{⇀}{K}}_{m} = {\overset{⇀}{k}}_{i, m} - {\overset{⇀}{k}}_{d, m}, & | {\overset{⇀}{k}}_{i, m} | = | {\overset{⇀}{k}}_{d, m} | = \frac{2 π n}{λ}, \begin{matrix} m = 1, 2 \end{matrix}; \end{matrix}

where

{\overset{⇀}{K}}_{m}

is the grating vector of the m-th hologram, λ denotes propagation wavelength in free space, and n is the refractive index of the recording material. Figure 2(a) shows the k-sphere diagrams for two multiplexed gratings within a single volume hologram in the imaging system in 2D space. Two incident beams from different depths propagate along the optical axis (z) and diffract at different angles (Δθ = 1^ο) after being Bragg matched to their corresponding multiplexed gratings. In Fig. 2(b), because of the Bragg degeneracy property, a holographic grating can be probed in degenerate fashion by dθ with a mis-matched wavelength dλ for imaging. The dispersion relationship of the Bragg degeneracy could be written as [23],

d θ / d λ = K / 4 π n \sin (α - θ),

where α and θ are the angles of grating vector and incident beam, with respect to the normal to surface of a MVHGs, respectively.

Fig. 2 The Bragg K-sphere diagram related to the diffracted geometry of a MVHGs with two gratings: (a) the geometry of the resultant k-sphere representation and collector lens on side-view from y-axis, and (b) Bragg wavelength degeneracy with a blue recording laser (|k_sig,₁| = |k_ref,₁| = 2πn/λ, λ = 488nm) and probing with green wavelength. (|k_fluo,i,₁| = |k _fluo,d,₁| = 2πn/λ_fluo, λ_fluo = 530nm).

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Based on the Bragg degeneracy property of Eq. (2), with broadband light-induced fluorescently labeled object, the diffracted viewing angle expands along the x-direction, and thus the system’s field-of-view (FoV) is increased with broadband emitting light. Figure 1(c) shows two depth-resolved images of fluorescently labeled microspheres with standard uniform illumination using an Argon gas laser operated at a wavelength of 488 nm. We used a hologram with two MVHGs of average diffraction efficiency of ~40%. Admittedly, with more MVHGs, the average efficiency might be lower, but the efficiency can be enhanced using silicon oxide nanoparticles doped PQ-PMMA. Essentially, there is a trade-off between the number of imaging depths and the FoV of each depth plane. However, the FoV in the lateral (x) dimension varies depending on the hologram design and the spectral bandwidth of the emitted light. Therefore, rather than viewing more depths within an object, cameras with large pixel counts can be utilized to have wider FoV with less imaging depths.

2.2. Normal HiLo computational principle with speckle illumination

With broadband emission, such as a fluorescently labeled object, depth selectivity using the MVHGs degrades proportionally to the fluorescence bandwidth. In Fig. 1(c), some micro-beads are selected, and circular shapes show blurred beads are out-of-focus, indicating poor depth selectivity under uniform illumination. Figure 1(d) shows that the speckle contrast on the in-focus microspheres is obviously clear, while the contrast on the defocused beads is barely observed. This inspires the use of HiLo based on active 3D speckle illumination to reduce the resulting scatter.

The HiLo principle [17] typically requires two images, one uniformly and one structured light illuminated images, to computationally reconstruct an optically sectioned image. The reconstructed resultant image is the combination of the in-focus high (Hi) frequency content extracted from the image under uniform illumination, and the in-focus low (Lo) frequency content extracted from the image with structured illumination. We modified the HiLo principle for our proposed speckle-based VHM system. Let $I_{u} (\vec{r}, d_{m})$ and $I_{s} (\vec{r}, d_{m})$ be the uniform and structured speckle illuminated images at the axial planes d_m acquired from the speckle-based VHM. The Hi and Lo images at the corresponding axial plane d_m, are given by [13]:

I_{H i} (\vec{r}, d_{m}) = ℑ^{- 1} {H P_{k_{c}, d_{m}} {ℑ [I_{u} (\vec{r}, d_{m})]}},

I_{L o} (\vec{r}, d_{m}) = ℑ^{- 1} {L P_{k_{c}, d_{m}} {ℑ [C_{δ s} \times I_{u} (\vec{r}, d_{m})]}} .

Then the speckle-based VHM image at the corresponding axial plane d_m can be reconstructed as:

I_{s p e c k l e - b a s e d \begin{matrix} V H M \end{matrix}} (\vec{r}, d_{m}) = I_{H i} (\vec{r}, d_{m}) + η_{d_{m}} \times I_{L o} (\vec{r}, d_{m}),

where

ℑ

and

ℑ^{- 1}

represent the Fourier and inverse Fourier transform operators, and m is the number of MVHGs.

C_{δ s}

can be expressed as [11]:

C_{δ s} (\vec{r}, d_{m}) = \frac{σ_{A} (I_{s} (\vec{r}, d_{m}) - I_{u} (\vec{r}, d_{m}))}{{〈 I_{u} (\vec{r}, d_{m}) 〉}_{A}},

where

σ_{A} (\cdot)

denotes the standard deviation operator of speckle variation between uniformly illuminated (I_u) and structured speckle illuminated (I_s) images, and

{〈 I_{u} (\vec{r}, d_{m}) 〉}_{A}

is the mean value of the uniformly illuminated image over the local resolved sampling window (A).

C_{δ s}

indicates the local speckle contrast between in-focus and out-of-focus region within A. With smaller sampling window,

C_{δ s}

may not be properly calculated without sufficient speckles, while larger sampling window the resultant images are similar to uniformly illuminated ones.

H P_{k_{c}, d_{m}}

and

L P_{k_{c}, d_{m}}

are the high-pass and low-pass filters with the cut-off frequency k_c relative to the sampling window at the axial plane d_m [24]. Essentially, the value of

η_{d_{m}}

depends on the contrast of the projected speckles. Typical values of

η_{d_{m}}

used for processing the images for our system are 0.5~3.5 for both planes.

2.3 Modified HiLo computational principle with wavelet filtering

Instead of increasing the spatial frequency of the projected speckle pattern at the object plane, we utilizes an additional wavelet filter with modified $C_{δ s}$ , filtering out imaged speckles with low contrast at defocus regions, to enhance system’s optical sectioning capability since I_s is an parameter of $C_{δ s}$ in Eq. (6). The modified $C_{δ s}$ for the wavelet filtering process is given by [7]:

C_{δ s, W} (\vec{r}, d_{m}) = \frac{σ_{A} {ℑ^{- 1} [W ({\vec{k}}_{⊥}) \times ℑ (I_{s} (\vec{r}, d_{m}) - I_{u} (\vec{r}, d_{m}))]}}{{〈 I_{u} (\vec{r}, d_{m}) 〉}_{A}},

where

W ({\vec{k}}_{⊥}) = \exp (- \frac{{\vec{k}}_{⊥}}{2 σ_{W}^{2}}) - \exp (- \frac{{\vec{k}}_{⊥}}{σ_{W}^{2}})

, and

{\vec{k}}_{⊥}

represents coordinates in spatial frequency domain. The standard deviation

σ_{W}

can be used to tune the high-pass region of

W ({\vec{k}}_{⊥})

, and the decay tendency of contrast values along the axial direction away from in-focus planes can also be numerically adjusted by changing the value of

σ_{W}

; therefore, the strength of the optical sectioning can be numerically manipulated by adjusting the value of

σ_{W}

[13]. Using this substitution for

C_{δ s, W}

into Eq. (4) to replace original

C_{δ s}

, the modified HiLo with wavelet filtering can then be applied to effectively enhance out-of-focus background rejection, which will be demonstrated in the experimental results section.

3. Experimental results and discussion

3.1 System performance for imaging fluorescent microspheres

The ability of the speckle-based VHM to resolve volumetric samples was verified by imaging fluorescently labeled 25µm microspheres (Polysciences), suspended in a 1 mm thick slab of agarose (Invitrogen). An optical diffuser (Luminit, KCN1-25) was used in the illumination to produce volumetric speckles within the sample for depth contrast and suppression of scattered light, while the MVHGs behaved as the spatial depth filter to simultaneously image multiple speckle-defined depths onto the CCD (Hamamatsu ORCA4.0 sCMOS) plane. The depth separation of the two MVHGs during imaging was ~50 µm. The microspheres were excited using a blue laser source (Innova 304C, Coherent Inc.) at λ = 488nm. A dichroic mirror (Q505lp, Chroma Technology Corp.) and an emission filter (MF530/43, Thorlabs Inc.) were utilized to reject stray excitation light during imaging. The speckled-VHM system had an effective magnification of 5.6 × using an Olympus objective lens (ULWDMSPlan50X) and a Mitutoyo imaging lens (MPlanAPO20X). Figure 3 performs the system’s depth resolution using normal HiLo process (blue dots and curve) and modified HiLo process (red dots and curve) with wavelet filtering. The decay of projected speckle contrast between the maximum and minimal intensity along the axial direction defines the optical sectioning capability of the speckle-based VHM system; therefore, this measurement was conducted with step size of 2 µm. The measured full width at half maximum (FWHM) with normal HiLo process is ~35 μm, and the FWHM with HiLo wavelet filtering process is ~25 μm. Therefore, without lateral and axial scanning, the speckle-based VHM system using HiLo process offers fine optical sectioning, and the system’s capability of out-of-focus background rejection is significantly enhanced with HiLo wavelet filtering. It is important to observe here that the imaging speckle contrast does not completely decay even up to the defocus range at 40μm. The proposed wavelet filtering method takes into account these low contrast defocus speckles by using $σ_{W}$ . A typical value of the cut-off frequency (k_c) with wavelet filtering used for processing the images is k_c~0.18 $σ_{W}$ [13].

Fig. 3 The axial contrast plot of the projected speckle image under bright field illumination condition representing the z point spread function using HiLo computational method without wavelet filtering (marked with blue color with FWHM ~35μm), and with wavelet filtering (marked with red color with FWHM ~25μm).

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To verify the ability of the speckle-based VHM for resolving volumetric samples, we conducted experiment by imaging ~25 µm size fluorescence labeled beads (Polyscience) suspended in a thick slab of agarose. Figures 4(a)-4(c) show the resultant two-depth resolved images using the standard uniform illumination, normal HiLo computational principle, and modified HiLo computational method with wavelet filtering, respectively. We used η = 1 for normal HiLo process, while η = 2.5, and $σ_{W} = 100$ with wavelet filtering. The sampling window A of a 10 × 10 (pixel²) matrix was selected for both HiLo process with wavelet filtering and without wavelet filtering. Figure 4(d) compares local contrast and out-of-focus background rejection, by plotting an intensity profile along a red line on the first plane, between the different techniques, while the comparison between local contrast and out-of-focus background rejection on the second plane along an orange line is shown in Fig. 4(e). The intensity of defocus microspheres is significantly suppressed using HiLo computational methods, especially through HiLo with wavelet filtering. Clearly, signal to background ratio is significant improved for the processed image at both the axial planes. However, as discussed in our previous work [25], the strength of in-focus signal is reduced for HiLo processing due to rejection of out-of-focus photons from the focal plane image reconstruction and thus no improvement in signal-to-noise ratio should be observed.

Fig. 4 (a) Resultant images of 25 µm fluorescence microspheres for two axial planes, separated at ~50µm, using uniform illumination. (b, c) Speckle-based VHM images at the corresponding axial planes, using pair-wise normal HiLo process (b), and (c) HiLo with wavelet filtering process. (d, e) Intensity profiles at the in-focus and out-of-focus microsphere along red line at depth 1 (d), and depth2 (e). The scalar bar indicated 50 µm.

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It is worth to mention that the proposed wavelet approach outperform normal HiLo method in suppressing the strong defocus background appears at plane 1. As discussed above, speckle contrast does not completely decay for certain defocus range, and thus conventional HiLo method is not able to completely suppress such defocus features. Wavelet approach effectively suppresses these low speckle contrast defocus features as described in section 2.3. Furthermore, for out-of-focus features with no speckle contrast, as presented at plane 2, similar performance is observed for wavelet and normal HiLo methods for defocus suppression. This leads to the contrast threshold of the detected speckle pattern, below which the proposed wavelet approach does not provide any further improvement over normal HiLo method.

3.2 Experimental results of imaging biological samples

In this experiment, an intestine sample was stained with Alexa-488 labeled Phalloidin for fluorescence labeling of actin proteins, and then imaged with the speckle-based VHM system. Figure 5 shows the images of villi of mouse intestine sample as taken with our speckle-based VHM system. As in the previous sparse case of the fluorescently labeled microspheres, two planes, separated by ~50 µm, were imaged simultaneously onto different parts of the camera. In this highly scattering case of the mice intestine sample, Fig. 5(a) was taken with uniform illumination, i.e. without the projected speckle pattern. The MVHGs still succeed at imaging the two planes, separated by ~50 µm, to adjacent regions of the camera. However, out-of-focus background is still visible due to the thick nature of the sample under the wide-field illumination. Figure 5(b) shows the effective removal of the out-of-focus background when we utilized the complete speckle-based VHM principle, including structured speckle illumination and HiLo wavelet post-processing. In Figs. 5(c) and 5(d), the images on the left show the resultant images with poor signal to background ratio, while the images on the right show relatively good signal to background ratio. It is clear that the haze (i.e. background) has been suppressed significantly such that low contrast features are now visible with good signal to background ratio. Figure 5(e) shows intensity cross-sections at depth 1 comparing the signal-to-background with uniform illumination and speckle-based VHM illumination.

Fig. 5 (a) Uniform illuminated images, and (b) Speckle-based VHM images of fluorescently labeled mice intestine sample, stained with Alexa-488 labeled Phalloidin, for the two axial depths. (c, d) Zoom-in image of the box-marked region of (a) and (b) at depth 1 and depth 2, respectively. (e) Intensity cross-section along the orange line shown in depth 1 of the uniformly illuminated and speckle-based VHM illuminated images (a). The scalar bar indicates 100µm size.

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4. Conclusions

We have developed a non-scanning, multi-plane, wide-field optical sectioning microscope, based on spatial-spectral MVHGs in combination with 3D structured speckle illumination. The proposed speckle-based VHM is simple and robust to simultaneously observe images from different planes within a volumetric tissue sample while effectively rejecting out-of-focus background. It is worth mentioning that the depth separation can be arbitrarily arranged with properly projected speckles. However, the depth separation of MVHGs should be larger than the FWHM of depth resolution in order to avoid the out-of-focus background between each depth and remain effective performance of optical sectioning. In addition, the speckle-based VHM is significantly faster than alternatives, requiring only two shots with no axial scanning to capture multiple planes simultaneously. Although in the current system two different depths are acquired, the system can be extended to obtain more planes simultaneously with more MVHGs [20]. Furthermore, it is possible to speed up the process of reconstructing multi-plane images through a faster computation device, such as a graphic processing unit (GPU), to enable real-time 3D video capture for in vivo biological applications, and to be adapted to a multi-plane, wide-field optical sectioning endoscopic format.

Acknowledgments

The authors gratefully acknowledge the support from the following sponsors: Taiwan Ministry of Science and Technology (100-2218-E-002-026-MY3, 102-2218-E-002-013-MY3, 103-2221-E-002-156-MY3), National Health Research Institutes (EX103-10220EC), National Taiwan University (102R7832), National Taiwan University Hospital (MP03, UN103-028), and National Research Foundation, Singapore through the Singapore MIT Alliance for Research and Technology's BioSystems and Micromechanics Inter-Disciplinary Research programme (015824-039).

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Speckle-based volume holographic microscopy for optically sectioned multi-plane fluorescent imaging

Abstract

1. Introduction

2. Method

2.1 Multiplexed volume holographic gratings (MVHGs) for fluorescence imaging

2.2. Normal HiLo computational principle with speckle illumination

2.3 Modified HiLo computational principle with wavelet filtering

3. Experimental results and discussion

3.1 System performance for imaging fluorescent microspheres

3.2 Experimental results of imaging biological samples

4. Conclusions

Acknowledgments

References and links

Cited By

Figures (5)

Equations (7)

Optics Express