Ultra-thin 3D lensless fiber endoscopy using diffractive optical elements and deep neural networks

Kuschmierz, Robert; Scharf, Elias; Ortegón-González, David F.; Glosemeyer, Tom; Czarske, Jürgen

doi:10.37188/lam.2021.030

Cited by 38 publications

(21 citation statements)

References 59 publications

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“…The stability of the system when bending the fiber bundle is a critical attribute for in vivo applications. Slight deformation of the fiber bundle after the reference measurement would lead to an additional global tilt of the image plane on the detection side 37 , 52 . The resulting tilt on the phase reconstruction, which is extracted from the background, can be further corrected numerically.…”

Section: Discussionmentioning

confidence: 99%

Quantitative phase imaging through an ultra-thin lensless fiber endoscope

Sun

et al. 2022

Light Sci Appl

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Quantitative phase imaging (QPI) is a label-free technique providing both morphology and quantitative biophysical information in biomedicine. However, applying such a powerful technique to in vivo pathological diagnosis remains challenging. Multi-core fiber bundles (MCFs) enable ultra-thin probes for in vivo imaging, but current MCF imaging techniques are limited to amplitude imaging modalities. We demonstrate a computational lensless microendoscope that uses an ultra-thin bare MCF to perform quantitative phase imaging with microscale lateral resolution and nanoscale axial sensitivity of the optical path length. The incident complex light field at the measurement side is precisely reconstructed from the far-field speckle pattern at the detection side, enabling digital refocusing in a multi-layer sample without any mechanical movement. The accuracy of the quantitative phase reconstruction is validated by imaging the phase target and hydrogel beads through the MCF. With the proposed imaging modality, three-dimensional imaging of human cancer cells is achieved through the ultra-thin fiber endoscope, promising widespread clinical applications.

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Section: Discussionmentioning

confidence: 99%

Quantitative phase imaging through an ultra-thin lensless fiber endoscope

Sun

et al. 2022

Light Sci Appl

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“…As an alternative approach, lensless cameras using lightmodulating masks have been recently proposed and demonstrated [9]- [27]. Instead of using lenses to form images on the image sensor, lensless cameras use amplitude-or phase masks with known light-modulating properties and rely on computational algorithms to reconstruct the scene from the sensor's measurement, achieving ultra-thin, light, and scalable formfactor at a low cost.…”

Section: Introductionmentioning

confidence: 99%

“…However, phase maskbased lensless cameras using weak diffusers [28] or designed diffractive elements [19] have higher light collection efficiency, less computational complexity in image reconstruction, better image quality, and multiplexing capabilities. With these advantages, a wide range of lensless imaging applications have been recently reported, including photography(photorealistic, video from stills, hyperspectral) [18], [24], microscopy [13], [21], [25], light-field imaging [26], 3D imaging [19], and endoscopy [14], [27].…”

Section: Introductionmentioning

confidence: 99%

Fabrication of Integrated Lensless Cameras via UV-Imprint Lithography

et al. 2022

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We report on the construction of a lensless camera with a phase-modulating mask layer integrated directly on an image sensor using the UV-imprint lithography method. By replicating the master phase mask's surface structure directly on the image sensor, our method further simplifies the fabrication of lensless cameras and delivers a rigid and durable device with a small form factor. Our prototype device has an open-faced design without any apertures and generates high-quality photographic reconstructions with high light collection efficiency. We analyze the performance of our prototype device and demonstrate various imaging applications, including the digital refocusing capabilities.

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“…We present a diffuser-based CFB endoscope in combination with a neural network for 2D image reconstruction at video rate. The setup is also capable of 3D reconstruction [8]. The reconstruction performance of different network architectures is compared regarding correlation coefficient (CC), peak signal-to-noise-ratio (PSNR) and structural similarity (SSIM).…”

Section: Introductionmentioning

confidence: 99%

Single-shot 3D endoscopic imaging exploiting a diffuser and neural networks

et al. 2022

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Lens-based endoscopes offer high lateral resolution, but suffer from rigid imaging properties, such as a fixed focal plane. We present a miniaturized 0.5 mm diameter endoscope in which the objective lens is replaced by an optical diffuser. The intensity information of the object space is scattered and passed to a camera via a coherent fibre bundle. The image is reconstructed by a neural network. The field of view and resolution depend on the object distance. 3D-single-shot imaging up to video rate can be enabled. The approach shows great potential for applications like robust 3D fluorescence imaging.

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Ultra-thin 3D lensless fiber endoscopy using diffractive optical elements and deep neural networks

Cited by 38 publications

References 59 publications

Quantitative phase imaging through an ultra-thin lensless fiber endoscope

Quantitative phase imaging through an ultra-thin lensless fiber endoscope

Fabrication of Integrated Lensless Cameras via UV-Imprint Lithography

Single-shot 3D endoscopic imaging exploiting a diffuser and neural networks

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