Unlike conventional fiber facet imaging methods, where imaging resolution is limited by the core-to-core spacing (Fig. We propose a novel computational approach named the far-field amplitude-only speckle transfer (FAST) method to decode the incident light field from the far-field speckles. ![]() In this research, we found that the MCF can directly work as a phase encoder without a coded aperture 29 at the measurement side, encoding the incident complex light field to a speckle pattern in the far-field at the detection side. Furthermore, an endoscope with nanoscale sensitivity of the optical path length is not yet reported, therefore, a simple and cost-effective 3D microendoscope with nanoscale sensitivity is highly demanded. In practice, bulky and expensive optical systems with spatial light modulators and complicated calibration processes are still required, and the scanning-based imaging technique can be slow, inducing many limitations for clinical applications. Coherent imaging is achieved via multi-mode fibers with transmission matrix measurement 31, 32 or wavefront shaping 33, 34, 35, 36, 37, 38, and similar approaches are also applied to MCF-based coherent imaging 39, 40, 41, 42, 43, 44, 45. Despite computational methods that have been proposed to recover the 3D information of samples 28, 29, 30, precise QPI via MCF with nanoscale sensitivity is still challenging. However, the phase information of the sample is lost due to the incoherent illumination. 1a, b), and recent advances in MCF-based computational imaging demonstrate the great potential of fiber bundles to be the next generation microendoscopes with minimal invasiveness 25, 26, 27. Multi-core fiber bundle (MCF) is an ultra-thin fiber bundle of a few hundred micrometers consisting of thousands of single-mode fiber cores (Fig. In clinical diagnosis, endoscopes with diameters of a few millimeters are commonly used for in vivo imaging. ![]() Such invasive approaches limit the in vivo application of QPI in clinical diagnosis, especially in the early diagnosis of cancer and tumors. On the other hand, current QPI methods are mostly based on bulky and expensive microscope platforms with limited working distance and penetration depth, which means invasive sampling or sectioning of diseased tissues or organs are required for pathological diagnosis 23, 24. Recent research combining QPI with deep learning has been used for virtual staining 18, 19 and dynamic blood examination 20, 21, which was reported as a high throughput approach to detecting the SARS-CoV-2 virus 22. Meanwhile, quantitative biophysical parameters such as refractive index 11, 12, dry mass 13, 14, matter density 15, and skewness 16 can be extracted from the quantitative phase shift, providing both morphological and quantitative biophysical information for digital pathology 17. ![]() 3D images of transparent samples can be reconstructed with QPI in a non-invasive manner 2, 3, 4, 5, 6, 7, 8, 9, 10, enabling nanoscale sensitivity to morphology and dynamics. Quantitative phase imaging (QPI) is an effective and label-free method for cell and tissue imaging in biomedicine 1. With the proposed imaging modality, three-dimensional imaging of human cancer cells is achieved through the ultra-thin fiber endoscope, promising widespread clinical applications. The accuracy of the quantitative phase reconstruction is validated by imaging the phase target and hydrogel beads through the MCF. 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. ![]() 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. Multi-core fiber bundles (MCFs) enable ultra-thin probes for in vivo imaging, but current MCF imaging techniques are limited to amplitude imaging modalities. However, applying such a powerful technique to in vivo pathological diagnosis remains challenging. Quantitative phase imaging (QPI) is a label-free technique providing both morphology and quantitative biophysical information in biomedicine.
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