Light-field micro-endoscopy using a fiber bundle: a snapshot 3D epi-fluorescence endoscope

Xiong, Bo; Song, Weizhi; Zhang, Xu; Zheng, Guoan; Dai, Qionghai; Cao, Xun

doi:10.1364/prj.464051

Cited by 8 publications

(6 citation statements)

References 35 publications

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“…Compared with other three-dimensional (3D) imaging methods recording a sequence of two-dimensional (2D) images to form a 3D volume such as light sheet microscopy (LSM) [6][7][8] , confocal microscopy 9,10 , and twophoton microscopy (2PM) 2 . LFM benefits from the advantages of single-shot acquisition manner, easyto-build optical set-up, and low phototoxicity [1][2][3][4][11][12][13] . LFM utilizes a microlens array (MLA) inserted in the detection path of a commonly-used epi-fluorescence microscopy to encode the 3D volumetric information in a snapshot acquisition 13 .…”

Section: Introductionmentioning

confidence: 99%

Aberration modeling in deep learning for volumetric reconstruction of light-field microscopy

Jin

Zhao

Xiong

et al. 2023

Preprint

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Optical aberration is a crucial issue in optical microscopes, which fundamentally limits the practical imaging performance. As a commonly encountered one, spherical aberration is introduced by the refractive index mismatches between samples and environments, which will cause problems like low contrast, blurring, and distortion in imaging. Light-field microscopy (LFM) has recently emerged as a powerful tool for fast volumetric imaging. The appearance of spherical aberration in LFM will cause large changes of the point spread function (PSF) and thus greatly affects the imaging performance. Here, we propose the aberration-modeling view-channel-depth (AM-VCD) network for LFM reconstruction, which can well mitigate the influence of large spherical aberration. By quantitatively estimating the spherical aberration in advance and modeling it in the network training, the AM-VCD can obtain aberration-corrected high-speed visualization of three-dimensional (3D) processes with uniform spatial resolution and real-time reconstruction speed. Without any hardware modification, our method provides a convenient way to directly observe the 3D dynamics of samples in solution. We demonstrate the capability of AM-VCD under a large refractive index mismatch with volumetric imaging of a large-scale fishbone of largemouth bass. We further investigate the capability of AM-VCD in real-time volumetric imaging of dynamic zebrafish for tracking neutrophil migration.

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Section: Introductionmentioning

confidence: 99%

Aberration modeling in deep learning for volumetric reconstruction of light-field microscopy

Jin

Zhao

Xiong

et al. 2023

Preprint

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“…Meanwhile, it is also hoped to detect further information on the cellular tissues in the lesion area, so it is necessary to enable it with the function of depth-of-field (DOF) detection. 18,19 The MLA requires less surface roughness for optical performance, whereas the hydrophobic structure, especially the superhydrophobic one, demands more roughness. Now, two approaches are generally adopted to achieve the hydrophobic property of the MLA.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, when the medical endoscope is used in surgery, the fluid environment inside the human body will bring a greater impact on the imaging effect, so it is also urgently necessary to enable it with the waterproof property. Meanwhile, it is also hoped to detect further information on the cellular tissues in the lesion area, so it is necessary to enable it with the function of depth-of-field (DOF) detection. , …”

Section: Introductionmentioning

confidence: 99%

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Superhydrophobic Multifocal Microlens Array with Depth-of-Field Detection for a Humid Environment

Cao,

Deng,

Wan

et al. 2023

ACS Omega

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Microlens array (MLA) has been widely applied in augmented reality and optical imaging. When used in a humid environment or medical endoscopy, MLA needs to be both superhydrophobic and multifocal. However, it is not easy to achieve both superhydrophobic and multifocal function by integrating superhydrophobic and multifocal structures on the same surface by means of a simple, efficient, and precise method. In this paper, the superhydrophobic multifocal MLA with superhydrophobic properties and multifocal functions is successfully designed for preparation based on a method of 3D lithography and soft lithography. The 3D lithography can further help the preparation of a multifocal MLA with varying apertures and a multistep superhydrophobic structure with a round dome. The superhydrophobic multifocal MLA with periods 50 and 120 μm has perfect superhydrophobic property. The water droplet can slide and bounce off the surface at a roll angle of less than 12.9° with both multifocal and integrated imaging function, as well as up to 397 μm depth-of-field (DOF) detection range; this greatly exceeds the conventional MLA. The perfect superhydrophobic and optical property can be achieved in an extremely humid environment. The superhydrophobic multifocal MLA proposed in this paper has a promising prospect for actual practices.

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“…In comparison, LFM benefits from the advantages of single-shot acquisition manner, easy-to-build optical set-up, and low photobleaching and phototoxicity. [1][2][3][4]15,18,19] LFM utilizes a microlens array (MLA) inserted in the detection path of a commonly-used epifluorescence microscopy to encode the 3D volumetric information in a snapshot acquisition. [19] Then by postprocessing the snapshot with deconvolution [20] or learning-based [21,22] methods, high-speed volumetric imaging of various applications can be obtained with promising performance.…”

Section: Introductionmentioning

confidence: 99%

Aberration Modeling in Deep Learning for Volumetric Reconstruction of Light‐Field Microscopy

Zhou,

Jin,

Zhao

et al. 2023

Laser & Photonics Reviews

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Optical aberration is a crucial issue in optical microscopes, fundamentally constraining the achievable imaging performance. As a commonly encountered one, spherical aberration is introduced by the refractive index mismatches between samples and their surrounding environments, leading to problems like low contrast, blurring, and distortion in imaging. Light‐field microscopy (LFM) has recently emerged as a powerful tool for rapid volumetric imaging. The presence of spherical aberration in LFM will cause substantial changes of the point spread function (PSF) and thus greatly affects the imaging performance. Here, the aberration‐modeling view‐channel‐depth (AM‐VCD) network is proposed for LFM reconstruction, effectively mitigating the influence of severe spherical aberration. By quantitatively estimating the spherical aberration in advance and incorporating it into the network training, the AM‐VCD achieves aberration‐corrected high‐speed visualization of 3D processes with uniform spatial resolution and real‐time reconstruction speed. Without necessitating hardware modifications, this method provides a convenient way for directly observing the 3D dynamics of samples in solution. The capability of AM‐VCD under a large refractive index mismatch is demonstrated through volumetric imaging of a large‐scale fishbone of a largemouth bass. Furthermore, the capability of AM‐VCD in nearly 100 Hz volumetric imaging of neutrophil migration and a beating heart in living zebrafish is investigated.

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Light-field micro-endoscopy using a fiber bundle: a snapshot 3D epi-fluorescence endoscope

Cited by 8 publications

References 35 publications

Aberration modeling in deep learning for volumetric reconstruction of light-field microscopy

Aberration modeling in deep learning for volumetric reconstruction of light-field microscopy

Superhydrophobic Multifocal Microlens Array with Depth-of-Field Detection for a Humid Environment

Aberration Modeling in Deep Learning for Volumetric Reconstruction of Light‐Field Microscopy

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