Swept-source Raman spectroscopy of chemical and biological materials.

Significance: Raman spectroscopy has been used as a powerful tool for chemical analysis, enabling the noninvasive acquisition of molecular fingerprints from various samples. Raman spectroscopy has proven to be valuable in numerous fields, including pharmaceutical, materials science, and biomedicine. Active research and development efforts are currently underway to bring this analytical instrument into the field, enabling in situ Raman measurements for a wider range of applications. Dispersive Raman spectroscopy using a fixed, narrowband source is a common method for acquiring Raman spectra. However, dispersive Raman spectroscopy requires a bulky spectrometer, which limits its field applicability. Therefore, there has been a tremendous need to develop a portable and sensitive Raman system. Aim: We developed a compact swept-source Raman (SS-Raman) spectroscopy system and proposed a signal processing method to mitigate hardware limitations. We demonstrated the capabilities of the SS-Raman spectroscopy by acquiring Raman spectra from both chemical and biological samples. These spectra were then compared with Raman spectra obtained using a conventional dispersive Raman spectroscopy system. Approach: The SS-Raman spectroscopy system used a wavelength-swept source laser (822 to 842 nm), a bandpass filter with a bandwidth of 1.5 nm, and a low-noise silicon photoreceiver. Raman spectra were acquired from various chemical samples, including phenylalanine, hydroxyapatite, glucose, and acetaminophen. A comparative analysis with the conventional dispersive Raman spectroscopy was conducted by calculating the correlation coefficients between the spectra from the SS-Raman spectroscopy and those from the conventional system. Furthermore, Raman mapping was obtained from cross-sections of swine tissue, demonstrating the applicability of the SS-Raman spectroscopy in biological samples. Results: We developed a compact SS-Raman system and validated its performance by acquiring Raman spectra from both chemical and biological materials. Our straightforward signal processing method enhanced the quality of the Raman spectra without incurring high costs. Raman spectra in the range of 900 to 1200 cm-1 were observed for phenylalanine, hydroxyapatite, glucose, and acetaminophen. The results were validated with correlation coefficients of 0.88, 0.84, 0.87, and 0.73, respectively, compared with those obtained from dispersive Raman spectroscopy. Furthermore, we performed scans across the cross-section of swine tissue to generate a biological tissue mapping plot, providing information about the composition of swine tissue. Conclusions: We demonstrate the capabilities of the proposed compact SS-Raman spectroscopy system by obtaining Raman spectra of chemical and biological materials, utilizing straightforward signal processing. We anticipate that the SS-Raman spectroscopy will be utilized in various fields, including biomedical and chemical applications.

Macrophage-mannose-receptor-targeted photoactivatable agent for in vivo imaging and treatment of atherosclerosis.

Previous studies have demonstrated the effects of theranostic agents on atherosclerotic plaques. However, there is limited information on targeted theranostics for photodynamic treatment of atherosclerosis. This study aimed to develop a macrophage-mannose-receptor-targeted photoactivatable nanoagent that regulates atherosclerosis and to evaluate its efficacy as well as safety in atherosclerotic mice. We synthesised and characterised D-mannosamine (MAN)-polyethylene glycol (PEG)-chlorin e6 (Ce6) for phototheranostic treatment of atherosclerosis. The diagnostic and therapeutic effects of MAN-PEG-Ce6 were investigated using the atherosclerotic mouse model. The hydrophobic Ce6 photosensitiser was surrounded by the hydrophilic MAN-PEG outer shell of the self-assembled nanostructure under aqueous conditions. The MAN-PEG-Ce6 was specifically internalised in macrophage-derived foam cells through receptor-mediated endocytosis. After laser irradiation, the MAN-PEG-Ce6 markedly increased singlet oxygen generation. Intravital imaging and immunohistochemistry analyses verified MAN-PEG-Ce6's specificity to plaque macrophages and its notable anti-inflammatory impact by effectively reducing mannose-receptor-positive macrophages. The toxicity assay showed that MAN-PEG-Ce6 had negligible effects on the biochemical profile and structural damage in the skin and organs. Targeted photoactivation with MAN-PEG-Ce6 thus has the potential to rapidly reduce macrophage-derived inflammatory responses in atheroma and present favourable toxicity profiles, making it a promising approach for both imaging and treatment of atherosclerosis.

Imaging peritoneal blood vessels through optical coherence tomography angiography for laparoscopic surgery.

Laparoscopic surgery presents challenges in identifying blood vessels due to lack of tactile feedback. The image-guided laparoscopic surgical tool (IGLaST) integrated with optical coherence tomography (OCT) has potential for in vivo blood vessel imaging; however, distinguishing vessels from surrounding tissue remains a challenge. In this study, we propose utilizing an inter-A-line intensity differentiation-based OCT angiography (OCTA) to improve visualization of blood vessels. By evaluating a tissue phantom with varying flow speeds, we optimized the system's blood flow imaging capabilities in terms of minimum detectable flow and contrast-to-noise ratio. In vivo experiments on rat and porcine models, successfully visualized previously unidentified blood vessels and concealed blood flows beneath the 1 mm depth peritoneum. Qualitative comparison of various OCTA algorithms indicated that the intensity differentiation-based algorithm performed best for our application. We believe that implementing IGLaST with OCTA can enhance surgical outcomes and reduce procedure time in laparoscopic surgeries.

Feasibility and safety of non-contrast optical coherence tomography imaging using hydroxyethyl starch in coronary arteries.

Intracoronary optical coherence tomography (OCT) requires injection of flushing media for image acquisition. Alternative flushing media needs to be investigated to reduce the risk of contrast-induced renal dysfunction. We investigated the feasibility and safety of pentastarch (hydroxyethyl starch) for clinical OCT imaging. We prospectively enrolled 43 patients with 70 coronary lesions (46-stented; 24-native). Total 81 OCT pullback pairs were obtained by manual injection of iodine contrast, followed by pentastarch. Each pullback was assessed frame-by-frame using an automated customized lumen contour/stent strut segmentation algorithm. Paired images were compared for the clear image segments (CIS), blood-flushing capability, and quantitative morphometric measurements. Overall image quality, as assessed by the proportion of CIS, was comparable between the contrast- and pentastarch-flushed images (97.1% vs. 96.5%; p = 0.160). The pixel-based blood-flushing capability was similar between the groups (0.951 [0.947-0.953] vs. 0.950 [0.948-0.952], p = 0.125). Quantitative two- and three-dimensional morphometric measurements of the paired images correlated well (p < 0.001) with excellent inter-measurement variability. All patients safely underwent OCT imaging using pentastarch without resulting in clinically relevant complications or renal deterioration. Non-contrast OCT imaging using pentastarch is clinically safe and technically feasible with excellent image quality and could be a promising alternative strategy for patients at high risk of renal impairment.

SNR enhanced high-speed two-photon microscopy using a pulse picker and time gating detection.

Two-photon microscopy (TPM) is an attractive biomedical imaging method due to its large penetration depth and optical sectioning capability. In particular, label-free autofluorescence imaging offers various advantages for imaging biological samples. However, relatively low intensity of autofluorescence leads to low signal-to-noise ratio (SNR), causing practical challenges for imaging biological samples. In this study, we present TPM using a pulse picker to utilize low pulse repetition rate of femtosecond pulsed laser to increase the pulse peak power of the excitation source leading to higher emission of two-photon fluorescence with the same average illumination power. Stronger autofluorescence emission allowed us to obtain higher SNR images of arterial and liver tissues. In addition, by applying the time gating detection method to the pulse signals obtained by TPM, we were able to significantly reduce the background noise of two-photon images. As a result, our TPM system using the pulsed light source with a 19 times lower repetition rate allowed us to obtain the same SNR image more than 19 times faster with the same average power. Although high pulse energy can increase the photobleaching, we also observed that high-speed imaging with low total illumination energy can mitigate the photobleaching effect to a level similar to that of conventional illumination with a high repetition rate. We anticipate that this simple approach will provide guidance for SNR enhancement with high-speed imaging in TPM as well as other nonlinear microscopy.

Ultra-thin light-weight laser-induced-graphene (LIG) diffractive optics.

The realization of hybrid optics could be one of the best ways to fulfill the technological requirements of compact, light-weight, and multi-functional optical systems for modern industries. Planar diffractive lens (PDL) such as diffractive lenses, photonsieves, and metasurfaces can be patterned on ultra-thin flexible and stretchable substrates and be conformally attached on top of arbitrarily shaped surfaces. In this review, we introduce recent research works addressed to the design and manufacturing of ultra-thin graphene optics, which will open new markets in compact and light-weight optics for next-generation endoscopic brain imaging, space internet, real-time surface profilometry, and multi-functional mobile phones. To provide higher design flexibility, lower process complexity, and chemical-free process with reasonable investment cost, direct laser writing (DLW) of laser-induced-graphene (LIG) is actively being applied to the patterning of PDL. For realizing the best optical performances in DLW, photon-material interactions have been studied in detail with respect to different laser parameters; the resulting optical characteristics have been evaluated in terms of amplitude and phase. A series of exemplary laser-written 1D and 2D PDL structures have been actively demonstrated with different base materials, and then, the cases are being expanded to plasmonic and holographic structures. The combination of these ultra-thin and light-weight PDL with conventional bulk refractive or reflective optical elements could bring together the advantages of each optical element. By integrating these suggestions, we suggest a way to realize the hybrid PDL to be used in the future micro-electronics surface inspection, biomedical, outer space, and extended reality (XR) industries.

Label-Free Characterization of Atherosclerotic Plaques Via High-Resolution Multispectral Fluorescence Lifetime Imaging Microscopy.

BACKGROUND: Autofluorescence lifetime (AFL) imaging, a robust technique that enables label-free molecular investigation of biological tissues, is being introduced into the field of cardiovascular diagnostics. However, detailed AFL characteristics of coronary arteries remain elusive and there is a lack of methodology enabling such characterization. METHODS: We developed multispectral fluorescence lifetime imaging microscopy (FLIM) based on analog-mean-delay. Freshly sectioned coronary arteries and atheromas, harvested from 5 swine models, were imaged using FLIM and stained to label lipids, macrophages, collagen, and smooth muscle cells. The components were quantitated from digitized histological images and compared with the corresponding FLIM. Multispectral AFL parameters derived from 2 different spectral bands (390 nm and 450 nm) were analyzed. RESULTS: FLIM provided a wide field-of-view, high-resolution AFL imaging of frozen sections. Principal compositions of coronary arteries, such as tunica media, tunica adventitia, elastic laminas, smooth muscle cell-enriched fibrous plaque, lipid-rich core, and foamy macrophages, were well visualized in FLIM images and were found to have each different AFL spectra. In particular, proatherogenic components including lipids and foamy macrophages exhibited significantly different AFL values compared with plaque-stabilizing collagen- or smooth muscle cell-enriched tissues (P<0.0001). Pairwise comparisons showed that each composition was distinguishable from another by the difference in multispectral AFL parameters. Pixel-level analysis based on coregistered FLIM-histology dataset showed that each component of atherosclerosis (lipids, macrophages, collagen, and smooth muscle cells) had distinct correlation pattern with AFL parameters. Random forest regressors trained with the dataset allowed automated, simultaneous visualization of the key atherosclerotic components with high accuracy (r>0.87). CONCLUSIONS: FLIM provided detailed pixel-level AFL investigation of the complex composition of coronary artery and atheroma. Our FLIM strategy enabling an automated, comprehensive visualization of multiple plaque components from unlabeled sections will be highly useful to efficiently evaluate ex vivo samples without the need for histological staining and analysis.

Deep learning-based image enhancement in optical coherence tomography by exploiting interference fringe.

Optical coherence tomography (OCT), an interferometric imaging technique, provides non-invasive, high-speed, high-sensitive volumetric biological imaging in vivo. However, systemic features inherent in the basic operating principle of OCT limit its imaging performance such as spatial resolution and signal-to-noise ratio. Here, we propose a deep learning-based OCT image enhancement framework that exploits raw interference fringes to achieve further enhancement from currently obtainable optimized images. The proposed framework for enhancing spatial resolution and reducing speckle noise in OCT images consists of two separate models: an A-scan-based network (NetA) and a B-scan-based network (NetB). NetA utilizes spectrograms obtained via short-time Fourier transform of raw interference fringes to enhance axial resolution of A-scans. NetB was introduced to enhance lateral resolution and reduce speckle noise in B-scan images. The individually trained networks were applied sequentially. We demonstrate the versatility and capability of the proposed framework by visually and quantitatively validating its robust performance. Comparative studies suggest that deep learning utilizing interference fringes can outperform the existing methods. Furthermore, we demonstrate the advantages of the proposed method by comparing our outcomes with multi-B-scan averaged images and contrast-adjusted images. We expect that the proposed framework will be a versatile technology that can improve functionality of OCT.

Massively parallel electro-optic sampling of space-encoded optical pulses for ultrafast multi-dimensional imaging.

High-speed and high-resolution imaging of surface profiles is critical for the investigation of various structures and mechanical dynamics of micro- and nano-scale devices. In particular, recent emergence of various nonlinear, transient and complex mechanical dynamics, such as anharmonic vibrations in mechanical resonators, has necessitated real-time surface deformation imaging with higher axial and lateral resolutions, speed, and dynamic range. However, real-time capturing of fast and complex mechanical dynamics has been challenging, and direct time-domain imaging of displacements and mechanical motions has been a missing element in studying full-field structural and dynamic behaviours. Here, by exploiting the electro-optic sampling with a frequency comb, we demonstrate a line-scan time-of-flight (TOF) camera that can simultaneously measure the TOF changes of more than 1000 spatial coordinates with hundreds megapixels/s pixel-rate and sub-nanometre axial resolution over several millimetres field-of-view. This unique combination of performances enables fast and precise imaging of both complex structures and dynamics in three-dimensional devices and mechanical resonators.

Histological classification of atherosclerotic arteries using high-speed confocal Raman microscopy with machine learning.

Confocal Raman microscopy is a useful tool to observe composition and constitution of label-free samples at high spatial resolution. However, accurate characterization of microstructure of tissue and its application in diagnostic imaging are challenging due to weak Raman scattering signal and complex chemical composition of tissue. We have developed a method to improve imaging speed, diffraction efficiency, and spectral resolution of confocal Raman microscopy. In addition to the novel imaging technique, the machine learning method enables confocal Raman microscopy to visualize accurate histology of tissue sections. Here, we have demonstrated the performance of the proposed method by measuring histological classification of atherosclerotic arteries and compared the histological confocal Raman images with the conventional staining method. Our new confocal Raman microscopy enables us to comprehend the structure and biochemical composition of tissue and diagnose the buildup of atherosclerotic plaques in the arterial wall without labeling.

Method for improving the speed and pattern quality of a DMD maskless lithography system using a pulse exposure method.

Maskless lithography based on a digital micromirror device (DMD) has the advantages of high process flexibility and a low production cost. However, due to the trade-off relationship between the pixel size and exposure area, it is challenging to achieve high resolutions and high patterning speeds at the same time, which hinders the wider application of this technology in micro- and nano-fabrication processes. In addition, micromirrors in DMDs create pixelated edges that limit the pattern quality. In this paper, we propose a novel DMD maskless lithography method to improve the pattern quality during high-speed continuous patterning by means of pulse exposure and oblique scanning processes. A unique criterion, the pixel occupancy, was devised to determine the parameters related to the pulse exposure and oblique scanning optimally. We also studied how the duty cycle of the pulse exposure affects the pattern quality. As a result, we were able to increase the scanning speed up to the speed limit considering the damage threshold of the DMD and improve the pattern quality by resolving the pixelation problem. We anticipate that this method can be used in various microfabrication fields with short product life cycles or in those that require custom designs, such as the manufacturing of PCBs, MEMS devices, and micro-optics devices, among others.

Lateral image reconstruction of optical coherence tomography using one-dimensional deep deconvolution network.

BACKGROUND AND OBJECTIVES: Optical coherence tomography (OCT) is a cross-sectional imaging method utilizing a low coherence interferometry. The lateral resolution of the OCT is limited by the numerical aperture (NA) of the imaging lens. Using a high NA lens improves the lateral resolution but reduces the depth of focus (DOF). In this study, we propose a method to improve the lateral resolution of OCT images by end-to-end training of a deep 1-D deconvolution network without use of high-resolution images. MATERIALS AND METHODS: To improve the lateral resolution of the OCT, we trained the 1-D deconvolution network using lateral profiles of OCT images and the beam spot size. We used our image-guided laparoscopic surgical tool (IGLaST) to acquire OCT images of nonbiological and biological samples ex vivo. The OCT images were then blurred by applying Gaussian functions with various full width half maximums ranging from 40 to 160 µm. The network was trained using the blurred OCT images as input and the non-blurred original OCT images as output. We quantitatively evaluated the developed network in terms of similarity and signal-to-ratio (SNR), using in-vivo images of mesenteric tissue from a porcine model that was not used for training. In addition, we performed knife-edge tests and qualitative evaluation of the network to show the lateral resolution improvement of ex-vivo and in-vivo OCT images. RESULTS: The proposed method showed an improvement of image quality on both blurred images and non-blurred images. When the proposed deconvolution network was applied, the similarity to the non-blurred image was improved by 1.29 times, and the SNR was improved by 1.76 dB compared to the artificially blurred images, which was superior to the conventional deconvolution method. The knife-edge tests at distances at 200 to 1000 µm from the imaging probe showed an approximately 1.2 times improvement in lateral resolution. In addition, through qualitative evaluation, it was found that the image quality of both ex-vivo and in-vivo tissue images was improved with clear structure and less noise. CONCLUSIONS: This study showed the ability of the 1-D deconvolution network to improve the image quality of OCT images with variable lateral resolution. We were able to train the network with a small amount of data by constraining the network in 1-D. The quantitative evaluation showed better results than conventional deconvolution methods for various amount of blurring. Qualitative evaluation showed analogous results with quantitative results. This simple yet powerful image restoration method provides improved lateral resolution and suppresses background noise, making it applicable to a variety of OCT imaging applications.

Robust autofocusing for scanning electron microscopy based on a dual deep learning network.

Scanning electron microscopy (SEM) is a high-resolution imaging technique with subnanometer spatial resolution that is widely used in materials science, basic science, and nanofabrication. However, conducting SEM is rather complex due to the nature of using an electron beam and the many parameters that must be adjusted to acquire high-quality images. Only trained operators can use SEM equipment properly, meaning that the use of SEM is restricted. To broaden the usability of SEM, we propose an autofocus method for a SEM system based on a dual deep learning network, which consists of an autofocusing-evaluation network (AENet) and an autofocusing-control network (ACNet). The AENet was designed to evaluate the quality of given images, with scores ranging from 0 to 9 regardless of the magnification. The ACNet can delicately control the focus of SEM online based on the AENet's outputs for any lateral sample position and magnification. The results of these dual networks showed successful autofocus performance on three trained samples. Moreover, the robustness of the proposed method was demonstrated by autofocusing on unseen samples. We expect that our autofocusing system will not only contribute to expanding the versatility of SEM but will also be applicable to various microscopes.

Multimodal microscopy for the simultaneous visualization of five different imaging modalities using a single light source.

Optical microscopy has been widely used in biomedical research as it provides photophysical and photochemical information of the target in subcellular spatial resolution without requiring physical contact with the specimen. To obtain a deeper understanding of biological phenomena, several efforts have been expended to combine such optical imaging modalities into a single microscope system. However, the use of multiple light sources and detectors through separated beam paths renders previous systems extremely complicated or slow for in vivo imaging. Herein, we propose a novel high-speed multimodal optical microscope system that simultaneously visualizes five different microscopic contrasts, i.e., two-photon excitation, second-harmonic generation, backscattered light, near-infrared fluorescence, and fluorescence lifetime, using a single femtosecond pulsed laser. Our proposed system can visualize five modal images with a frame rate of 3.7 fps in real-time, thereby providing complementary optical information that enhances both structural and functional contrasts. This highly photon-efficient multimodal microscope system enables various properties of biological tissues to be assessed.

Targeted theranostic photoactivation on atherosclerosis.

BACKGROUND: Photoactivation targeting macrophages has emerged as a therapeutic strategy for atherosclerosis, but limited targetable ability of photosensitizers to the lesions hinders its applications. Moreover, the molecular mechanistic insight to its phototherapeutic effects on atheroma is still lacking. Herein, we developed a macrophage targetable near-infrared fluorescence (NIRF) emitting phototheranostic agent by conjugating dextran sulfate (DS) to chlorin e6 (Ce6) and estimated its phototherapeutic feasibility in murine atheroma. Also, the phototherapeutic mechanisms of DS-Ce6 on atherosclerosis were investigated. RESULTS: The phototheranostic agent DS-Ce6 efficiently internalized into the activated macrophages and foam cells via scavenger receptor-A (SR-A) mediated endocytosis. Customized serial optical imaging-guided photoactivation of DS-Ce6 by light illumination reduced both atheroma burden and inflammation in murine models. Immuno-fluorescence and -histochemical analyses revealed that the photoactivation of DS-Ce6 produced a prominent increase in macrophage-associated apoptotic bodies 1 week after laser irradiation and induced autophagy with Mer tyrosine-protein kinase expression as early as day 1, indicative of an enhanced efferocytosis in atheroma. CONCLUSION: Imaging-guided DS-Ce6 photoactivation was able to in vivo detect inflammatory activity in atheroma as well as to simultaneously reduce both plaque burden and inflammation by harmonic contribution of apoptosis, autophagy, and lesional efferocytosis. These results suggest that macrophage targetable phototheranostic nanoagents will be a promising theranostic strategy for high-risk atheroma.

Macrophage targeted theranostic strategy for accurate detection and rapid stabilization of the inflamed high-risk plaque.

Rationale: Inflammation plays a pivotal role in the pathogenesis of the acute coronary syndrome. Detecting plaques with high inflammatory activity and specifically treating those lesions can be crucial to prevent life-threatening cardiovascular events. Methods: Here, we developed a macrophage mannose receptor (MMR)-targeted theranostic nanodrug (mannose-polyethylene glycol-glycol chitosan-deoxycholic acid-cyanine 7-lobeglitazone; MMR-Lobe-Cy) designed to identify inflammatory activity as well as to deliver peroxisome proliferator-activated gamma (PPARγ) agonist, lobeglitazone, specifically to high-risk plaques based on the high mannose receptor specificity. The MMR-Lobe-Cy was intravenously injected into balloon-injured atheromatous rabbits and serial in vivo optical coherence tomography (OCT)-near-infrared fluorescence (NIRF) structural-molecular imaging was performed. Results: One week after MMR-Lobe-Cy administration, the inflammatory NIRF signals in the plaques notably decreased compared to the baseline whereas the signals in saline controls even increased over time. In accordance with in vivo imaging findings, ex vivo NIRF signals on fluorescence reflectance imaging (FRI) and plaque inflammation by immunostainings significantly decreased compared to oral lobeglitazone group or saline controls. The anti-inflammatory effect of MMR-Lobe-Cy was mediated by inhibition of TLR4/NF-κB pathway. Furthermore, acute resolution of inflammation altered the inflamed plaque into a stable phenotype with less macrophages and collagen-rich matrix. Conclusion: Macrophage targeted PPARγ activator labeled with NIRF rapidly stabilized the inflamed plaques in coronary sized artery, which could be quantitatively assessed using intravascular OCT-NIRF imaging. This novel theranostic approach provides a promising theranostic strategy for high-risk coronary plaques.

Utilization potential of intraluminal optical coherence tomography for the Eustachian tube.

Imaging the Eustachian tube is challenging because of its complex anatomy and limited accessibility. This study fabricated a fiber-based optical coherence tomography (OCT) catheter and investigated its potential for assessing the Eustachian tube anatomy. A customized OCT system and an imaging catheter, termed the Eustachian OCT, were developed for visualizing the Eustachian tube. Three male swine cadaver heads were used to study OCT image acquisition and for subsequent histologic correlation. The imaging catheter was introduced through the nasopharyngeal opening and reached toward the middle ear. The OCT images were acquired from the superior to the nasopharyngeal opening before and after Eustachian tube balloon dilatation. The histological anatomy of the Eustachian tube was compared with corresponding OCT images, The new, Eustachian OCT catheter was successfully inserted in the tubal lumen without damage. Cross-sectional images of the tube were successfully obtained, and the margins of the anatomical structures including cartilage, mucosa lining, and fat could be successfully delineated. After balloon dilatation, the expansion of the cross-sectional area could be identified from the OCT images. Using the OCT technique to assess the Eustachian tube anatomy was shown to be feasible, and the fabricated OCT image catheter was determined to be suitable for Eustachian tube assessment.

Color three-dimensional imaging based on patterned illumination using a negative pinhole array.

Reflectance confocal microscopy is widely used for non-destructive optical three-dimensional (3D) imaging. In confocal microscopy, a stack of sequential two-dimensional (2D) images with respect to the axial position is typically needed to reconstruct a 3D image. As a result, in conventional confocal microscopy, acquisition speed is often limited by the rate of mechanical scanning in both the transverse and axial directions. We previously reported a high-speed parallel confocal detection method using a pinhole array for color 3D imaging without any mechanical scanners. Here, we report a high-speed color 3D imaging method based on patterned illumination employing a negative pinhole array, whose optical characteristics are the reverse of the conventional pinhole array for transmitting light. The negative pinhole array solves the inherent limitation of a conventional pinhole array, i.e., low transmittance, meaning brighter color images with abundant color information can be acquired. We also propose a 3D image processing algorithm based on the 2D cross-correlation between the acquired image and filtering masks, to produce an axial response. By using four-different filtering masks, we were able to increase the sampling points in calculation of height and enhance the lateral resolution of the color acquisition by a factor of four. The feasibility of high-speed non-contact color 3D measurement with the improved lateral resolution and brightness provided by the negative pinhole array was demonstrated by imaging various specimens. We anticipate that this high-speed color 3D measurement technology with negative pinhole array will be a useful tool in a variety of fields where rapid and accurate non-contact measurement are required, such as industrial inspection and dental scanning.

Label-free multimodal microscopy using a single light source and detector for biological imaging.

Multimodal nonlinear microscopy has been widely applied in biology and medicine due to its relatively deep penetration into tissue and its label-free manner. However, current multimodal systems require the use of multiple sources and detectors, leading to bulky, complex, and expensive systems. In this Letter, we present a novel method of using a single light source and detector for nonlinear multimodal imaging of biological samples. Using a photonic crystal fiber, a pulse picker, and multimode fibers, our developed system successfully acquired multimodal images of swine coronary arteries, including two-photon excitation fluorescence, second-harmonic generation, coherent anti-Stokes Raman scattering, and backreflection. The developed system could be a valuable tool for various biomedical applications.