4.6 Article

Analysis of Deep Learning-Based Phase Retrieval Algorithm Performance for Quantitative Phase Imaging Microscopy

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Biochemical Research Methods

Analysis of the surface plasmon resonance interferometric imaging performance of scanning confocal surface plasmon microscopy

Sorawit Tontarawongsa et al.

Summary: In this study, the optical phase imaging performance of a scanning confocal surface plasmon microscope was analyzed using rigorous coupled-wave theory. Two imaging modes, non-quantitative imaging and quantitative imaging modes, were investigated. Compared to non-interferometric surface plasmon microscopes, the scanning confocal SPR microscope showed higher spatial resolution, better sensitivity, and lower crosstalk measurement. The confocal SPR microscope configuration is a strong candidate for high throughput measurements due to its smaller sensing channel requirement.

BIOMEDICAL OPTICS EXPRESS (2022)

Article Multidisciplinary Sciences

Measurement precision enhancement of surface plasmon resonance based angular scanning detection using deep learning

Kitsada Thadson et al.

Summary: In this study, a deep learning-based method is proposed to enhance the accuracy of plasmonic angle detection without the need for complex post-processing and curve fitting methods. The proposed network, trained using simulated reflectance spectra, is validated in experiments and achieves a higher measurement precision compared to traditional curve fitting methods.

SCIENTIFIC REPORTS (2022)

Article Engineering, Electrical & Electronic

Analysis of Open Grating-Based Fabry-Perot Resonance Structures With Potential Applications for Ultrasensitive Refractive Index Sensing

Suvicha Sasivimolkul et al.

Summary: A theoretical framework is presented to explain the characteristics of Fabry-Perot resonances excited in a thin film-based grating, with comparisons to other thin film-based interferometers for refractive index sensing applications. The proposed structure shows higher figure of merit and a wider dynamic range compared to conventional surface plasmon resonance and FP structures.

IEEE SENSORS JOURNAL (2021)

Article Optics

PhaseGAN: a deep-learning phase-retrieval approach for unpaired datasets

Yuhe Zhang et al.

Summary: PhaseGAN is a novel deep learning approach based on Generative Adversarial Networks, which allows for real-time phase reconstruction without paired datasets by incorporating image formation physics and a novel Fourier loss function, addressing the failure of traditional phase retrieval algorithms.

OPTICS EXPRESS (2021)

Article Multidisciplinary Sciences

Deep learning-based single-shot phase retrieval algorithm for surface plasmon resonance microscope based refractive index sensing application

Kitsada Thadson et al.

Summary: A deep learning algorithm for single-shot phase retrieval under a conventional microscope is proposed and demonstrated through surface plasmon resonance imaging. The algorithm, based on deep learning-based pattern recognition, shows lower detection limit compared to conventional surface plasmon resonance measurements for refractive index sensing, without the need for sophisticated optical interferometer instrumentation.

SCIENTIFIC REPORTS (2021)

Review Chemistry, Multidisciplinary

Surface Plasmon Resonance Microscopy: From Single-Molecule Sensing to Single-Cell Imaging

Xiao-Li Zhou et al.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2020)

Article Biochemistry & Molecular Biology

Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks

Todd C. Hollon et al.

NATURE MEDICINE (2020)

Article Engineering, Multidisciplinary

Defocus leakage radiation microscopy for single shot surface plasmon measurement

Terry W. K. Chow et al.

MEASUREMENT SCIENCE AND TECHNOLOGY (2020)

Article Computer Science, Artificial Intelligence

Mu-net: Multi-scale U-net for two-photon microscopy image denoising and restoration

Sehyung Lee et al.

NEURAL NETWORKS (2020)

Review Optics

Transport of intensity equation: a tutorial

Chao Zuo et al.

OPTICS AND LASERS IN ENGINEERING (2020)

Review Chemistry, Analytical

Recent Advances in Surface Plasmon Resonance Imaging Sensors

Dongping Wang et al.

SENSORS (2019)

Review Radiology, Nuclear Medicine & Medical Imaging

A gentle introduction to deep learning in medical image processing

Andreas Maier et al.

ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK (2019)

Article Optics

Quantitative phase imaging with molecular vibrational sensitivity

Miu Tamamitsu et al.

OPTICS LETTERS (2019)

Article Biochemistry & Molecular Biology

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis

Po-Hsuan Cameron Chen et al.

NATURE MEDICINE (2019)

Article Engineering, Electrical & Electronic

Characterization of Low Loss Waveguides Using Bragg Gratings

Yi-Wen Hu et al.

IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS (2018)

Review Optics

Quantitative phase imaging in biomedicine

YongKeun Park et al.

NATURE PHOTONICS (2018)

Article Optics

Single shot embedded surface plasmon microscopy with vortex illumination

Terry W. K. Chow et al.

OPTICS EXPRESS (2016)

Article Computer Science, Artificial Intelligence

On the Mathematical Properties of the Structural Similarity Index

Dominique Brunet et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2012)