Depth-enhanced 2-D optical coherence tomography using complex wavefront shaping.

We report the enhancement in the obtained signal and penetration depth of 2-D depth-resolved images that were taken by shaping the incident wavefront in optical coherence tomography (OCT). Limitations in the penetration depth and signal to noise ratio (SNR) in OCT are mainly due to multiple scattering, which have been effectively suppressed by controlling the incident wavefront using a digital mirror device (DMD) in combination with spectral-domain OCT. The successful enhancements in the penetration depth and SNR are demonstrated in a wide-range of tissue phantoms, reaching depth enhancement of up to 92%. The hidden structures inside a tissue phantom that could not be seen in conventional OCT are clearly revealed through our proposed system. Its 2-D imaging capability, assisted by further optimization of the system for real-time acquisition speed will boost wide-spread use of OCT for in-vivo tissue diagnosis.

Spectro-refractometry of individual microscopic objects using swept-source quantitative phase imaging.

We present a novel spectroscopic quantitative phase imaging technique with a wavelength swept-source, referred to as swept-source diffraction phase microscopy (ssDPM), for quantifying the optical dispersion of microscopic individual samples. Employing the swept-source and the principle of common-path interferometry, ssDPM measures the multispectral full-field quantitative phase imaging and spectroscopic microrefractometry of transparent microscopic samples in the visible spectrum with a wavelength range of 450-750 nm and a spectral resolution of less than 8 nm. With unprecedented precision and sensitivity, we demonstrate the quantitative spectroscopic microrefractometry of individual polystyrene beads, 30% bovine serum albumin solution, and healthy human red blood cells.

Complex wavefront shaping for optimal depth-selective focusing in optical coherence tomography.

We report on an approach to exploit multiple light scattering by shaping the incident wavefront in optical coherence tomography (OCT). Most of the reflected signal from biological tissue consists of multiply scattered light, which is regarded as noise in OCT. A digital mirror device (DMD) is utilized to shape the incident wavefront such that the maximal energy is focused at a specific depth in a highly scattering sample using a coherence-gated reflectance signal as feedback. The proof-of-concept experiment demonstrates that this approach enhances depth-selective focusing in the presence of optical inhomogeneity, and thus extends the penetration depth in spectral domain-OCT (SD-OCT).

Dynamic spectroscopic phase microscopy for quantifying hemoglobin concentration and dynamic membrane fluctuation in red blood cells.

We report a technique for simultaneous label-free quantification of cytoplasmic hemoglobin Hb concentration and dynamic membrane fluctuation in individual red blood cells (RBCs). Spectroscopic phase microscopy equipped with three different coherent laser sources and a color detector records three wavelength-dependent quantitative phase images in a single shot of a color-coded hologram. Using molecular specific dispersion, we demonstrate the extraction of Hb concentration and the dynamic membrane fluctuation from individual RBCs.

Polarization holographic microscopy for extracting spatio-temporally resolved Jones matrix.

We present a high-speed holographic microscopic technique for quantitative measurement of polarization light-field, referred to as polarization holographic microscopy (PHM). Employing the principle of common-path interferometry, PHM quantitatively measures the spatially resolved Jones matrix components of anisotropic samples with only two consecutive measurements of spatially modulated holograms. We demonstrate the features of PHM with imaging the dynamics of liquid crystal droplets at a video-rate.

Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning.

High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) can be acquired together with energy dispersive X-ray (EDX) spectroscopy to give complementary information on the nanoparticles being imaged. Recent deep learning approaches show potential for accurate 3D tomographic reconstruction for these applications, but a large number of high-quality electron micrographs are usually required for supervised training, which may be difficult to collect due to the damage on the particles from the electron beam. To overcome these limitations and enable tomographic reconstruction even in low-dose sparse-view conditions, here we present an unsupervised deep learning method for HAADF-STEM-EDX tomography. Specifically, to improve the EDX image quality from low-dose condition, a HAADF-constrained unsupervised denoising approach is proposed. Additionally, to enable extreme sparse-view tomographic reconstruction, an unsupervised view enrichment scheme is proposed in the projection domain. Extensive experiments with different types of quantum dots show that the proposed method offers a high-quality reconstruction even with only three projection views recorded under low-dose conditions.

Quantitative analysis of hemodynamic and metabolic changes in subcortical vascular dementia using simultaneous near-infrared spectroscopy and fMRI measurements.

Subcortical vascular dementia (SVD) is a form of vascular dementia from small vessel disease with white matter lesions and lacunes. We hypothesized that hemodynamic and metabolic changes in the cortex during a simple motor task may reflect the impaired neurovascular coupling in SVD. We used fMRI and near-infrared spectroscopy (NIRS) simultaneously, which together provided multiple hemodynamic responses as well as a robust estimation of the cerebral metabolic rate of oxygen (CMRO(2)). During the task periods, the oxy-hemoglobin, total-hemoglobin, blood oxygenation level-dependent (BOLD) response, cerebral blood flow (CBF), and CMRO(2) decreased statistically significantly in the primary motor and somatosensory cortices of SVD patients, whereas the oxygen extraction fraction increased when compared with controls. Notably, the flow-metabolism coupling ratio, n representing the ratio of oxygen supply to its utilization, showed a robust reduction in the SVD patient group (n(Control)=1.99 ± 0.23; n(SVD)=1.08 ± 0.24), which implies a loss of metabolic reserve. These results support the pathological small vessel compromise, including an increased vessel stiffness, impaired vascular reactivity, and impaired neurovascular coupling in SVD. In conclusion, simultaneous measurement by NIRS and fMRI can reveal various hemodynamic and metabolic changes and may be used for as an early detection or monitoring of SVD.

All-solid-state spatial light modulator with independent phase and amplitude control for three-dimensional LiDAR applications.

Spatial light modulators are essential optical elements in applications that require the ability to regulate the amplitude, phase and polarization of light, such as digital holography, optical communications and biomedical imaging. With the push towards miniaturization of optical components, static metasurfaces are used as competent alternatives. These evolved to active metasurfaces in which light-wavefront manipulation can be done in a time-dependent fashion. The active metasurfaces reported so far, however, still show incomplete phase modulation (below 360°). Here we present an all-solid-state, electrically tunable and reflective metasurface array that can generate a specific phase or a continuous sweep between 0 and 360° at an estimated rate of 5.4 MHz while independently adjusting the amplitude. The metasurface features 550 individually addressable nanoresonators in a 250 × 250 µm2 area with no micromechanical elements or liquid crystals. A key feature of our design is the presence of two independent control parameters (top and bottom gate voltages) in each nanoresonator, which are used to adjust the real and imaginary parts of the reflection coefficient independently. To demonstrate this array's use in light detection and ranging, we performed a three-dimensional depth scan of an emulated street scene that consisted of a model car and a human figure up to a distance of 4.7 m.

Self-reference quantitative phase microscopy for microfluidic devices.

This Letter describes a quantitative phase microscopy for microfluidic devices using a simple self-referencing interferometry. Compared with the gross dimensions of the microfluidic device, the microchannel occupies only a small area of the device. Hence, the reference field can be generated by inverting the relative position of the specimen and background. Our system is realized using an extended depth-of-field optics in the form of Michelson interferometry, which allows quantitative phase measurement for an increased depth-of-field without moving objective lens or specimen. Furthermore, the system can be readily converted to a higher signal-to-noise ratio Hilbert phase microscopy thanks to the simultaneous acquisition of double interferograms. The performance of our system is verified using polymer beads, micropatterning poly(dimethylsiloxane) (PDMS), and embryo cells in the microchannels.

NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy.

Near infrared spectroscopy (NIRS) is a non-invasive method to measure brain activity via changes in the degree of hemoglobin oxygenation through the intact skull. As optically measured hemoglobin signals strongly correlate with BOLD signals, simultaneous measurement using NIRS and fMRI promises a significant mutual enhancement of temporal and spatial resolutions. Although there exists a powerful statistical parametric mapping tool in fMRI, current public domain statistical tools for NIRS have several limitations related to the quantitative analysis of simultaneous recording studies with fMRI. In this paper, a new public domain statistical toolbox known as NIRS-SPM is described. It enables the quantitative analysis of NIRS signal. More specifically, NIRS data are statistically analyzed based on the general linear model (GLM) and Sun's tube formula. The p-values are calculated as the excursion probability of an inhomogeneous random field on a representation manifold that is dependent on the structure of the error covariance matrix and the interpolating kernels. NIRS-SPM not only enables the calculation of activation maps of oxy-, deoxy-hemoglobin and total hemoglobin, but also allows for the super-resolution localization, which is not possible using conventional analysis tools. Extensive experimental results using finger tapping and memory tasks confirm the viability of the proposed method.

Wavelet minimum description length detrending for near-infrared spectroscopy.

Near-infrared spectroscopy (NIRS) can be employed to investigate brain activities associated with regional changes of the oxy- and deoxyhemoglobin concentration by measuring the absorption of near-infrared light through the intact skull. NIRS is regarded as a promising neuroimaging modality thanks to its excellent temporal resolution and flexibility for routine monitoring. Recently, the general linear model (GLM), which is a standard method for functional MRI (fMRI) analysis, has been employed for quantitative analysis of NIRS data. However, the GLM often fails in NIRS when there exists an unknown global trend due to breathing, cardiac, vasomotion, or other experimental errors. We propose a wavelet minimum description length (Wavelet-MDL) detrending algorithm to overcome this problem. Specifically, the wavelet transform is applied to decompose NIRS measurements into global trends, hemodynamic signals, and uncorrelated noise components at distinct scales. The minimum description length (MDL) principle plays an important role in preventing over- or underfitting and facilitates optimal model order selection for the global trend estimate. Experimental results demonstrate that the new detrending algorithm outperforms the conventional approaches.

High-Performance and Industrially Feasible Ni-Rich Layered Cathode Materials by Integrating Coherent Interphase.

For developing the industrially feasible Ni-rich layered oxide cathode with extended cycle life, it is necessary to mitigate both the mechanical degradation due to intergranular cracking between primary particles and gas generation from the reaction between the electrolyte and residual Li in the cathode. To simultaneously resolve these two issues, we herein propose a simple but novel method to reinforce the primary particles in LiNi0.91Co0.06Mn0.03O2 by providing a Li-reactive material, whose spinel interphase is coherent with the surface of the cathode. The modified structure significantly outperforms analogous bare samples: they conserve more than 90% of the initial capacity after 50 cycles and also exhibit a greater rate capability. By tracking the same particle location during cycling, we confirmed that the current method significantly reduces crack generation because the provided coating material can penetrate inside the grain boundary of the secondary particle and help maintain the volume of the primary particle. Finally, first-principles calculations were implemented to determine the role of this spinel material, i.e., having intrinsically isotropic lattice parameters, superior mechanical properties, and only a small volume change during delithiation. We believe that the proposed method is straightforward and cost-effective; hence, it is directly applicable for the mass production of Ni-rich cathode material to enable its commercialization.

In vivo deep tissue imaging using wavefront shaping optical coherence tomography.

Multiple light scattering in tissue limits the penetration of optical coherence tomography (OCT) imaging. Here, we present in vivo OCT imaging of a live mouse using wavefront shaping (WS) to enhance the penetration depth. A digital micromirror device was used in a spectral-domain OCT system for complex WS of an incident beam which resulted in the optimal delivery of light energy into deep tissue. Ex vivo imaging of chicken breasts and mouse ear tissues showed enhancements in the strength of the image signals and the penetration depth, and in vivo imaging of the tail of a live mouse provided a multilayered structure inside the tissue.

Fluorescent microscopy beyond diffraction limits using speckle illumination and joint support recovery.

Structured illumination microscopy (SIM) breaks the optical diffraction limit by illuminating a sample with a series of line-patterned light. Recently, in order to alleviate the requirement of precise knowledge of illumination patterns, structured illumination microscopy techniques using speckle patterns have been proposed. However, these methods require stringent assumptions of the speckle statistics: for example, speckle patterns should be nearly incoherent or their temporal average should be roughly homogeneous. Here, we present a novel speckle illumination microscopy technique that overcomes the diffraction limit by exploiting the minimal requirement that is common for all the existing super-resolution microscopy, i.e. that the fluorophore locations do not vary during the acquisition time. Using numerical and real experiments, we demonstrate that the proposed method can improve the resolution up to threefold. Because our proposed method succeeds for standard fluorescence probes and experimental protocols, it can be applied in routine biological experiments.

Simple super-resolution live-cell imaging based on diffusion-assisted Förster resonance energy transfer.

Despite the recent development of several super-resolution fluorescence microscopic techniques, there are still few techniques that can be readily employed in conventional imaging systems. We present a very simple, rapid, general and cost-efficient super-resolution imaging method, which can be directly employed in a simple fluorescent imaging system with general fluorophores. Based on diffusion-assisted Förster resonance energy transfer (FRET), fluorescent donor molecules that label specific target structures can be stochastically quenched by diffusing acceptor molecules, thereby temporally separating otherwise spatially overlapped fluorescence signals and allowing super-resolution imaging. The proposed method provides two- to three-fold-enhancement in spatial resolution, a significant optical sectioning property, and favorable temporal resolution in live-cell imaging. We demonstrate super-resolution live-cell dynamic imaging using general fluorophores in a standard epi-fluorescence microscope with light-emitting diode (LED) illumination. Due to the simplicity of this approach, we expect that the proposed method will prove an attractive option for super-resolution imaging.

Quantification of CMRO(2) without hypercapnia using simultaneous near-infrared spectroscopy and fMRI measurements.

Estimation of the cerebral metabolic rate of oxygen (CMRO(2)) and cerebral blood flow (CBF) is important to investigate the neurovascular coupling and physiological components in blood oxygenation level-dependent (BOLD) signals quantitatively. Although there are methods that can determine CMRO(2) changes using functional MRI (fMRI) or near-infrared spectroscopy (NIRS), current approaches require a separate hypercapnia calibration process and have the potential to incur bias in many assumed model parameters. In this paper, a novel method to estimate CMRO(2) without hypercapnia is described using simultaneous measurements of NIRS and fMRI. Specifically, an optimization framework is proposed that minimizes the differences between the two forms of the relative CMRO(2)-CBF coupling ratio from BOLD and NIRS biophysical models, from which hypercapnia calibration and model parameters are readily estimated. Based on the new methods, we found that group average CBF, CMRO(2), cerebral blood volume (CBV), and BOLD changes within activation of the primary motor cortex during a finger tapping task increased by 39.5 +/- 21.4%, 18.4 +/- 8.7%, 12.9 +/- 6.7%, and 0.5 +/- 0.2%, respectively. The group average estimated flow-metabolism coupling ratio was 2.38 +/- 0.65 and the hypercapnia parameter was 7.7 +/- 1.7%. These values are within the range of values reported from other literatures. Furthermore, the activation maps from CBF and CMRO(2) were well localized on the primary motor cortex, which is the main target region of the finger tapping task.