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Fan G, Jiang C, Huang Z, Tian M, Pan H, Cao Y, Lei T, Luo Q, Yuan J. 3D autofluorescence imaging of hydronephrosis and renal anatomical structure using cryo-micro-optical sectioning tomography. Theranostics 2023; 13:4885-4904. [PMID: 37771780 PMCID: PMC10526660 DOI: 10.7150/thno.86695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 08/26/2023] [Indexed: 09/30/2023] Open
Abstract
Rationale: Mesoscopic visualization of the main anatomical structures of the whole kidney in vivo plays an important role in the pathological diagnosis and exploration of the etiology of hydronephrosis. However, traditional imaging methods cannot achieve whole-kidney imaging with micron resolution under conditions representing in vivo perfusion. Methods: We used in vivo cryofixation (IVCF) to fix acute obstructive hydronephrosis (unilateral ureteral obstruction, UUO), chronic spontaneous hydronephrosis (db/db mice), and their control mouse kidneys for cryo-micro-optical sectioning tomography (cryo-MOST) autofluorescence imaging. We quantitatively assessed the kidney-wide pathological changes in the main anatomical structures, including hydronephrosis, renal subregions, arteries, veins, glomeruli, renal tubules, and peritubular functional capillaries. Results: By comparison with microcomputed tomography imaging, we confirmed that IVCF can maintain the status of the kidney in vivo. Cryo-MOST autofluorescence imaging can display the main renal anatomical structures with a cellular resolution without contrast agents. The hydronephrosis volume reached 26.11 ± 6.00 mm3 and 13.01 ± 3.74 mm3 in 3 days after UUO and in 15-week-old db/db mouse kidneys, respectively. The volume of the cortex and inner stripe of the outer medulla (ISOM) increased while that of the inner medulla (IM) decreased in UUO mouse kidneys. Db/db mice also showed an increase in the volume of the cortex and ISOM volume but no atrophy in the IM. The diameter of the proximal convoluted tubule and proximal straight tubule increased in both UUO and db/db mouse kidneys, indicating that proximal tubules were damaged. However, some renal tubules showed abnormal central bulge highlighting in the UUO mice, but the morphology of renal tubules was normal in the db/db mice, suggesting differences in the pathology and severity of hydronephrosis between the two models. UUO mouse kidneys also showed vascular damage, including segmental artery and vein atrophy and arcuate vein dilation, and the density of peritubular functional capillaries in the cortex and IM was reduced by 37.2% and 49.5%, respectively, suggesting renal hypoxia. In contrast, db/db mouse kidneys showed a normal vascular morphology and peritubular functional capillary density. Finally, we found that the db/db mice displayed vesicoureteral reflux and bladder overactivity, which may be the cause of hydronephrosis formation. Conclusions: We observed and compared main renal structural changes in hydronephrosis under conditions representing in vivo perfusion in UUO, db/db, and control mice through cryo-MOST autofluorescence imaging. The results indicate that cryo-MOST with IVCF can serve as a simple and powerful tool to quantitatively evaluate the in vivo pathological changes in three dimensions, especially the distribution of body fluids in the whole kidney. This method is potentially applicable to the three-dimensional visualization of other tissues, organs, and even the whole body, which may provide new insights into pathological changes in diseases.
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Affiliation(s)
- Guoqing Fan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Chenyu Jiang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Zhuoyao Huang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Mingyu Tian
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Huijuan Pan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yaru Cao
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Tian Lei
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainmatics, JITRI, Suzhou 215123, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainmatics, JITRI, Suzhou 215123, China
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Chen X, Zhong S, Hou Y, Cao R, Wang W, Li D, Dai Q, Kim D, Xi P. Superresolution structured illumination microscopy reconstruction algorithms: a review. LIGHT, SCIENCE & APPLICATIONS 2023; 12:172. [PMID: 37433801 DOI: 10.1038/s41377-023-01204-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 05/24/2023] [Accepted: 06/05/2023] [Indexed: 07/13/2023]
Abstract
Structured illumination microscopy (SIM) has become the standard for next-generation wide-field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view, and long-term imaging. Over the past decade, SIM hardware and software have flourished, leading to successful applications in various biological questions. However, unlocking the full potential of SIM system hardware requires the development of advanced reconstruction algorithms. Here, we introduce the basic theory of two SIM algorithms, namely, optical sectioning SIM (OS-SIM) and superresolution SIM (SR-SIM), and summarize their implementation modalities. We then provide a brief overview of existing OS-SIM processing algorithms and review the development of SR-SIM reconstruction algorithms, focusing primarily on 2D-SIM, 3D-SIM, and blind-SIM. To showcase the state-of-the-art development of SIM systems and assist users in selecting a commercial SIM system for a specific application, we compare the features of representative off-the-shelf SIM systems. Finally, we provide perspectives on the potential future developments of SIM.
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Affiliation(s)
- Xin Chen
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Suyi Zhong
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Yiwei Hou
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Ruijie Cao
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Wenyi Wang
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China
| | - Dong Li
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing, China
- Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China
- Beijing Key Laboratory of Multidimension & Multiscale Computational Photography, Tsinghua University, Beijing, China
- Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, Beijing, China
| | - Donghyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-Ro, Seodaemun-Gu, Seoul, 03722, Korea
| | - Peng Xi
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China.
- National Biomedical Imaging Center, Peking University, Beijing, 100871, China.
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Qiao W, Li Y, Ning K, Luo Q, Gong H, Yuan J. Differential synthetic illumination based on multi-line detection for resolution and contrast enhancement of line confocal microscopy. OPTICS EXPRESS 2023; 31:16093-16106. [PMID: 37157695 DOI: 10.1364/oe.491422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Line confocal (LC) microscopy is a fast 3D imaging technique, but its asymmetric detection slit limits resolution and optical sectioning. To address this, we propose the differential synthetic illumination (DSI) method based on multi-line detection to enhance the spatial resolution and optical sectioning capability of the LC system. The DSI method allows the imaging process to simultaneously accomplish on a single camera, which ensures the rapidity and stability of the imaging process. DSI-LC improves X- and Z-axis resolution by 1.28 and 1.26 times, respectively, and optical sectioning by 2.6 times compared to LC. Furthermore, the spatially resolved power and contrast are also demonstrated by imaging pollen, microtubule, and the fiber of the GFP fluorescence-labeled mouse brain. Finally, Video-rate imaging of zebrafish larval heart beating in a 665.6 × 332.8 µm2 field-of-view is achieved. DSI-LC provides a promising approach for 3D large-scale and functional imaging in vivo with improved resolution, contrast, and robustness.
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Yoon T, Kim PU, Ahn H, Kim T, Eom TJ, Kim K, Choi JR. Resolution-enhanced optical inspection system to examine metallic nanostructures using structured illumination. APPLIED OPTICS 2022; 61:6819-6826. [PMID: 36255761 DOI: 10.1364/ao.457806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/15/2022] [Indexed: 06/16/2023]
Abstract
We developed a structured illumination-based optical inspection system to inspect metallic nanostructures in real time. To address this, we used post-image-processing techniques to enhance the image resolution. To examine the fabricated metallic nanostructures in real time, a compact and highly resolved optical inspection system was designed for practical industrial use. Structured illumination microscopy yields multiple images with various linear illumination patterns, which can be used to reconstruct resolution-enhanced images. Images of nanosized posts and complex structures reflected in the structured illumination were reconstructed into images with improved resolution. A comparison with wide-field images demonstrates that the optical inspection system exhibits high performance and is available as a real-time nanostructure inspection platform. Because it does not require special environmental conditions and enables multiple systems to be covered in arrays, the developed system is expected to provide real-time and noninvasive inspections during the production of large-area nanostructured components.
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Deng L, Chen J, Li Y, Han Y, Fan G, Yang J, Cao D, Lu B, Ning K, Nie S, Zhang Z, Shen D, Zhang Y, Fu W, Wang WE, Wan Y, Li S, Feng YQ, Luo Q, Yuan J. Cryo-Fluorescence Micro-Optical Sectioning Tomography for Volumetric Imaging of Various Whole Organs with Subcellular Resolution. iScience 2022; 25:104805. [PMID: 35992061 PMCID: PMC9389242 DOI: 10.1016/j.isci.2022.104805] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 06/17/2022] [Accepted: 07/15/2022] [Indexed: 11/20/2022] Open
Abstract
Optical visualization of complex microstructures in the entire organ is essential for biomedical research. However, the existing methods fail to accurately acquire the detailed microstructures of whole organs with good morphological and biochemical preservation. This study proposes a cryo-fluorescence micro-optical sectioning tomography (cryo-fMOST) to image whole organs in three dimensions (3D) with submicron resolution. The system comprises a line-illumination microscope module, cryo-microtome, three-stage refrigeration module, and heat insulation device. To demonstrate the imaging capacity and wide applicability of the system, we imaged and reconstructed various organs of mice in 3D, including the healthy tongue, kidney, and brain, as well as the infarcted heart. More importantly, imaged brain slices were performed sugar phosphates determination and fluorescence in situ hybridization imaging to verify the compatibility of multi-omics measurements. The results demonstrated that cryo-fMOST is capable of acquiring high-resolution morphological details of various whole organs and may be potentially useful for spatial multi-omics. Cryo-fluorescence micro-optical sectioning tomography (Cryo-fMOST) was achieved 3D imaging of whole mouse tongue, kidney, heart, and brain at submicron resolution Frozen state well preserves tissues’ original morphology and biochemical information Cryo-fMOST is compatible with sugar phosphates determination and FISH measurement
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Affiliation(s)
- Lei Deng
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jianwei Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yafeng Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yutong Han
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Guoqing Fan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jie Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Dongjian Cao
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Bolin Lu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Kefu Ning
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Shuo Nie
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Zoutao Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Dan Shen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yunfei Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Wenbin Fu
- Department of Cardiology, Daping Hospital, Army Medical University, Chongqing 400038, China
| | - Wei Eric Wang
- Department of Cardiology, Daping Hospital, Army Medical University, Chongqing 400038, China
| | - Ying Wan
- Biomedical Analysis Center, Army Medical University, Chongqing 400038, China
- Chongqing Key Laboratory of Cytomics, Chongqing 400038, China
| | - Sha Li
- Department of Chemistry, Wuhan University, Wuhan 430072, China
- School of Public Health, Wuhan University, Wuhan 430071, China
| | - Yu-Qi Feng
- Department of Chemistry, Wuhan University, Wuhan 430072, China
- School of Public Health, Wuhan University, Wuhan 430071, China
| | - Qingming Luo
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
- Corresponding author
| | - Jing Yuan
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Innovation Institute, Huazhong University of Science and Technology, Wuhan 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215123, China
- Corresponding author
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Fu Z, Chen J, Liu G, Chen SC. Single-shot optical sectioning microscopy based on structured illumination. OPTICS LETTERS 2022; 47:814-817. [PMID: 35167532 DOI: 10.1364/ol.451267] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 01/04/2022] [Indexed: 06/14/2023]
Abstract
In this Letter, we present a single-shot 3D-resolved structured illumination microscopy (SIM) based on a digital micromirror device (DMD), a galvanometric mirror, and the HiLo algorithm. During imaging, the DMD rapidly generates sinusoidal and plane illuminations in the focal region. By synchronizing the DMD with a galvanometric scanner and exploiting the unique data readout process of the camera, the emissions from the specimen under two different illuminations, i.e., structured and uniform illumination, are projected to different regions on a camera, achieving high-resolution single-exposure optical sectioning at the camera's limiting speed, i.e., 200 Hz, without sacrificing the resolution. A model has been developed to guide the design and optimization of the optical system. Imaging experiments on pollen and mouse kidney samples have been performed to verify the predicted performance. The results show that the single-shot SIM with the HiLo algorithm achieves comparable resolution to the standard two-shot HiLo method with a twofold speed enhancement, which may find important applications in biophotonics, e.g., visualizing high-speed biological events in vivo.
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Huang C, Ching-Roa V, Liu Y, Giacomelli MG. High-speed mosaic imaging using scanner-synchronized stage position sampling. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:016502. [PMID: 35075830 PMCID: PMC8786391 DOI: 10.1117/1.jbo.27.1.016502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
SIGNIFICANCE Two-photon and confocal microscopy can obtain high frame rates; however, mosaic imaging of large tissue specimens remains time-consuming and inefficient, with higher imaging rates leading to a larger fraction of time wasted translating between imaging locations. Strip scanning obtains faster mosaic imaging rates by translating a specimen at constant velocity through a line scanner at the expense of more complex stitching and geometric distortion due to the difficulty of translating at completely constant velocity. AIM We aim to develop an approach to mosaic imaging that can obtain higher accuracy and faster imaging rates while reducing computational complexity. APPROACH We introduce an approach based on scanner-synchronous position sampling that enables subwavelength accurate imaging of specimens moving at a nonuniform velocity, eliminating distortion. RESULTS We demonstrate that this approach increases mosaic imaging rates while reducing computational complexity, retaining high SNR, and retaining geometric accuracy. CONCLUSIONS Scanner synchronous strip scanning enables accurate, high-speed mosaic imaging of large specimens by reducing acquisition and processing time.
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Affiliation(s)
- Chi Huang
- University of Rochester, Department of Biomedical Engineering, Rochester, New York, United States
| | - Vincent Ching-Roa
- University of Rochester, Department of Biomedical Engineering, Rochester, New York, United States
| | - Yihan Liu
- University of Rochester, Institute of Optics, Rochester, New York, United States
| | - Michael G. Giacomelli
- University of Rochester, Department of Biomedical Engineering, Rochester, New York, United States
- University of Rochester, Institute of Optics, Rochester, New York, United States
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Shi R, Zhang Y, Zhou T, Kong L. HiLo Based Line Scanning Temporal Focusing Microscopy for High-Speed, Deep Tissue Imaging. MEMBRANES 2021; 11:membranes11080634. [PMID: 34436397 PMCID: PMC8400873 DOI: 10.3390/membranes11080634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 01/12/2023]
Abstract
High-speed, optical-sectioning imaging is highly desired in biomedical studies, as most bio-structures and bio-dynamics are in three-dimensions. Compared to point-scanning techniques, line scanning temporal focusing microscopy (LSTFM) is a promising method that can achieve high temporal resolution while maintaining a deep penetration depth. However, the contrast and axial confinement would still be deteriorated in scattering tissue imaging. Here, we propose a HiLo-based LSTFM, utilizing structured illumination to inhibit the fluorescence background and, thus, enhance the image contrast and axial confinement in deep imaging. We demonstrate the superiority of our method by performing volumetric imaging of neurons and dynamical imaging of microglia in mouse brains in vivo.
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Affiliation(s)
- Ruheng Shi
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China;
| | - Yuanlong Zhang
- Department of Automation, Tsinghua University, Beijing 100084, China; (Y.Z.); (T.Z.)
| | - Tiankuang Zhou
- Department of Automation, Tsinghua University, Beijing 100084, China; (Y.Z.); (T.Z.)
- Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
| | - Lingjie Kong
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China;
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- Correspondence:
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