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Sun J, Wu J, Wu S, Goswami R, Girardo S, Cao L, Guck J, Koukourakis N, Czarske JW. Quantitative phase imaging through an ultra-thin lensless fiber endoscope. LIGHT, SCIENCE & APPLICATIONS 2022; 11:204. [PMID: 35790748 PMCID: PMC9255502 DOI: 10.1038/s41377-022-00898-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 06/10/2022] [Accepted: 06/16/2022] [Indexed: 05/29/2023]
Abstract
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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Affiliation(s)
- Jiawei Sun
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany.
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany.
| | - Jiachen Wu
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, 100084, Beijing, China
| | - Song Wu
- Institute for Integrative Nanosciences, IFW Dresden, Helmholtzstraße 20, 01069, Dresden, Germany
| | - Ruchi Goswami
- Max Planck Institute for the Science of Light & Max-Planck-Zentrum für Physik und Medizin, 91058, Erlangen, Germany
| | - Salvatore Girardo
- Max Planck Institute for the Science of Light & Max-Planck-Zentrum für Physik und Medizin, 91058, Erlangen, Germany
| | - Liangcai Cao
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, 100084, Beijing, China
| | - Jochen Guck
- Max Planck Institute for the Science of Light & Max-Planck-Zentrum für Physik und Medizin, 91058, Erlangen, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
| | - Nektarios Koukourakis
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany.
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany.
| | - Juergen W Czarske
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany.
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany.
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany.
- Institute of Applied Physics, TU Dresden, Dresden, Germany.
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Sun J, Wu J, Koukourakis N, Cao L, Kuschmierz R, Czarske J. Real-time complex light field generation through a multi-core fiber with deep learning. Sci Rep 2022; 12:7732. [PMID: 35546604 PMCID: PMC9095618 DOI: 10.1038/s41598-022-11803-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 04/28/2022] [Indexed: 12/26/2022] Open
Abstract
The generation of tailored complex light fields with multi-core fiber (MCF) lensless microendoscopes is widely used in biomedicine. However, the computer-generated holograms (CGHs) used for such applications are typically generated by iterative algorithms, which demand high computation effort, limiting advanced applications like fiber-optic cell manipulation. The random and discrete distribution of the fiber cores in an MCF induces strong spatial aliasing to the CGHs, hence, an approach that can rapidly generate tailored CGHs for MCFs is highly demanded. We demonstrate a novel deep neural network-CoreNet, providing accurate tailored CGHs generation for MCFs at a near video rate. The CoreNet is trained by unsupervised learning and speeds up the computation time by two magnitudes with high fidelity light field generation compared to the previously reported CGH algorithms for MCFs. Real-time generated tailored CGHs are on-the-fly loaded to the phase-only spatial light modulator (SLM) for near video-rate complex light fields generation through the MCF microendoscope. This paves the avenue for real-time cell rotation and several further applications that require real-time high-fidelity light delivery in biomedicine.
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Affiliation(s)
- Jiawei Sun
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany. .,Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany.
| | - Jiachen Wu
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany. .,State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing, 100084, China.
| | - Nektarios Koukourakis
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany.,Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
| | - Liangcai Cao
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing, 100084, China
| | - Robert Kuschmierz
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany.,Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
| | - Juergen Czarske
- Laboratory of Measurement and Sensor System Technique (MST), TU Dresden, Helmholtzstrasse 18, 01069, Dresden, Germany. .,Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany. .,Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany. .,Institute of Applied Physics, TU Dresden, Dresden, Germany.
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Panusa G, Dinc NU, Psaltis D. Photonic waveguide bundles using 3D laser writing and deep neural network image reconstruction. OPTICS EXPRESS 2022; 30:2564-2577. [PMID: 35209393 DOI: 10.1364/oe.446775] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 12/24/2021] [Indexed: 06/14/2023]
Abstract
In recent years, three-dimensional (3D) printing with multi-photon laser writing has become an essential tool for the manufacturing of three-dimensional optical elements. Single-mode optical waveguides are one of the fundamental photonic components, and are the building block for compact multicore fiber bundles, where thousands of single-mode elements are closely packed, acting as individual pixels and delivering the local information to a sensor. In this work, we present the fabrication of polymer rectangular step-index (STIN) optical waveguide bundles in the IP-Dip photoresist, using a commercial 3D printer. Moreover, we reduce the core-to-core spacing of the imaging bundles by means of a deep neural network (DNN) which has been trained with a large synthetic dataset, demonstrating that the scrambling of information due to diffraction and cross-talk between fiber cores can be undone. The DNN-based approach can be adopted in applications such as on-chip platforms and microfluidic systems where accurate imaging from in-situ printed fiber bundles suffer cross-talk. In this respect, we provide a design and fabrication guideline for such scenarios by employing the DNN not only as a post-processing technique but also as a design optimization tool.
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Rothe S, Daferner P, Heide S, Krause D, Schmieder F, Koukourakis N, Czarske JW. Benchmarking analysis of computer generated holograms for complex wavefront shaping using pixelated phase modulators. OPTICS EXPRESS 2021; 29:37602-37616. [PMID: 34808829 DOI: 10.1364/oe.434842] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 09/24/2021] [Indexed: 06/13/2023]
Abstract
Wavefront shaping with spatial light modulators (SLMs) enables aberration correction, especially for light control through complex media, like biological tissues and multimode fibres. High-fidelity light field shaping is associated with the calculation of computer generated holograms (CGHs), of which there are a variety of algorithms. The achievable performance of CGH algorithms depends on various parameters. In this paper, four different algorithms for CGHs are presented and compared for complex light field generation. Two iterative, double constraint Gerchberg-Saxton and direct search, and the two analytical, superpixel and phase encoding, algorithms are investigated. For each algorithm, a parameter study is performed varying the modulator's pixel number and phase resolution. The analysis refers to mode field generation in multimode fibre endoscopes and communication. This enables generality by generating specific mode combinations according to certain spatial frequency power spectra. Thus, the algorithms are compared varying spatial frequencies applied to different implementation scenarios. Our results demonstrate that the choice of algorithms has a significant impact on the achievable performance. This comprehensive study provides the required guide for CGH algorithm selection, improving holographic systems towards multimode fibre endoscopy and communications.
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Sun J, Koukourakis N, Guck J, Czarske JW. Rapid computational cell-rotation around arbitrary axes in 3D with multi-core fiber. BIOMEDICAL OPTICS EXPRESS 2021; 12:3423-3437. [PMID: 34221669 PMCID: PMC8221929 DOI: 10.1364/boe.423035] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 05/08/2021] [Accepted: 05/10/2021] [Indexed: 05/25/2023]
Abstract
Optical trapping is a vital tool in biology, allowing precise optical manipulation of nanoparticles, micro-robots, and cells. Due to the low risk of photodamage and high trap stiffness, fiber-based dual-beam traps are widely used for optical manipulation of large cells. Besides trapping, advanced applications like 3D refractive index tomography need a rotation of cells, which requires precise control of the forces, for example, the acting-point of the forces and the intensities in the region of interest (ROI). A precise rotation of large cells in 3D about arbitrary axes has not been reported yet in dual-beam traps. We introduce a novel dual-beam optical trap in which a multi-core fiber (MCF) is transformed to a phased array, using wavefront shaping and computationally programmable light. The light-field distribution in the trapping region is holographically controlled within 0.1 s, which determines the orientation and the rotation axis of the cell with small retardation. We demonstrate real-time controlled rotation of HL60 cells about all 3D axes with a very high degree of freedom by holographic controlled light through an MCF with a resolution close to the diffraction limit. For the first time, the orientation of the cell can be precisely controlled about all 3D axes in a dual-beam trap. MCFs provide much higher flexibility beyond the bulky optics, enabling lab-on-a-chip applications and can be easily integrated for applications like contactless cell surgery, refractive index tomography, cell-elasticity measurement, which require precise 3D manipulation of cells.
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Affiliation(s)
- Jiawei Sun
- Laboratory of Measurement and Sensor System Technique, TU Dresden, Helmholtzstrasse 18, 01069 Dresden, Germany
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
| | - Nektarios Koukourakis
- Laboratory of Measurement and Sensor System Technique, TU Dresden, Helmholtzstrasse 18, 01069 Dresden, Germany
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
| | - Jochen Guck
- Max Planck Institute for the Science of Light, Staudtstrasse 2, 91058 Erlangen, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
| | - Jürgen W. Czarske
- Laboratory of Measurement and Sensor System Technique, TU Dresden, Helmholtzstrasse 18, 01069 Dresden, Germany
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
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