Katalog : Details
 | Jiawei SunLearning-based Three-Dimensional Optical Cell Rotation Tomography and Quantitative Phase Imaging Using Multi-Core Fibers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| ISBN: | 978-3-8440-9052-9 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Reihe: | Dresdner Berichte zur Messsystemtechnik Herausgeber: Prof. Dr.-Ing. habil. Jürgen Czarske Dresden | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Band: | 19 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Schlagwörter: | optical manipulation; multi-core fiber; dual-beam trap; 3D cell rotation; holographic control; optical tomography; volumetric reconstruction; autonomous tomographic reconstruction; fiber endoscopes; speckle reconstruction; quantitative phase imaging; deep | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Publikationsart: | Dissertation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Sprache: | Englisch | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Seiten: | 158 Seiten | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abbildungen: | 70 Abbildungen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Gewicht: | 215 g | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Format: | 21 x 14,8 cm | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Bindung: | Paperback | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Preis: | 48,80 € / 61,10 SFr | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Erscheinungsdatum: | April 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kaufen: | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DOI: | 10.2370/9783844090529 (Online-Gesamtdokument) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Zusammenfassung: | Optical manipulation, which uses optical force to trap, move and rotate micro-or nanoscale objects, has led to remarkable advances in biology, physics, optics, and nanotechnology. Fiber-based dual-beam traps enable optical manipulation in a lab-on-a-chip system and have emerged as a vital manipulation tool for biological cells due to the low risk of photodamage. Nevertheless, optically controlled three-dimensional rotation of biological cells in a fiber-optic trap remains challenging.
In this dissertation, I demonstrate a novel multi-core fiber-based dual-beam trap, allowing three-dimensional cell rotation in a program-controlled manner. To achieve this, the multi-core fiber is transformed into a remote phased array by compensating the intrinsic and temporal phase distortion using a comprehensive in-situ calibration procedure. A dedicated phase retrieval algorithm and a phase encoder deep neural network are further implemented to generate the tailored phase modulation hologram for complex wavefront shaping through the multi-core fiber with high fidelity of 96.2\%, enabling real-time holographic control of the optical manipulation beam. This allows optically controlled rotation of human cancer cells about arbitrary axes in three dimensions. On the other hand, conventional illumination scanning optical tomography can hardly measure the full spatial frequency due to the limited projection angle, known as the missing cone problem, resulting in low axial resolution. The proposed fiber-optic cell rotation is implemented in optical projection tomography to overcome the problem, allowing accurate high-resolution volumetric reconstruction. Furthermore, an autonomous tomographic reconstruction workflow based on computer vision technologies and machine learning is employed for robust three-dimensional tomographic reconstruction of the rotated cell. Moreover, due to physical limitations, lens-based fiber endoscopes are difficult to further reduce the probe size to the sub-millimeter range while maintaining imaging resolution. A novel speckle reconstruction algorithm is proposed to achieve quantitative phase imaging through the multi-core fiber with up to 1~µm lateral resolution and nanoscale axial sensitivity, allowing label-free three-dimensional endoscopic imaging with minimum invasiveness smaller than 0.5 mm. Deep learning is further utilized to optimize the computation speed and measurement procedure, enabling real-time phase reconstruction through the fiber. This allows online measurement of the refractive index distribution of the cell in the optical trap, which can be implemented to generate the spatially optimized trapping beam for optical manipulation. The presented work provides innovative methods and new insights into optical manipulation, tomography, and fiber endoscopic imaging, opening new perspectives for future applications using multi-core fibers. I expect that our achievements in optical field control and imaging of multi-core fibers will expand their applications in clinical diagnostics, optogenetics, biosensors, integrated quantum photonic devices, and telecommunications. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
