Review
Biochemical Research Methods
Dickson M. D. Siu, Kelvin C. M. Lee, Bob M. F. Chung, Justin S. J. Wong, Guoan Zheng, Kevin K. K. Tsia
Summary: Propelled by advances in optical microscopy and deep learning, imaging in lab-on-a-chip has transformed from inspection to a smart engine. Advanced optical microscopes enable imaging across spatial scales and time windows. DL algorithms have revolutionized image processing and analysis. This article reviews the latest trends in optofluidic imaging and discusses how to integrate imaging techniques and DL algorithms for lab-on-a-chip applications. The potential synergisms in image formation, analytics, and autonomous lab-on-a-chip are highlighted.
Article
Multidisciplinary Sciences
Helen E. Parker, Sanghamitra Sengupta, Achar Harish, Ruben R. G. Soares, Haakan N. Joensson, Walter Margulis, Aman Russom, Fredrik Laurell
Summary: Microfluidics, specifically droplet microfluidics, is a rapidly developing field that offers independent manipulation and high-throughput analysis of droplets. In this study, we propose an optofluidic Lab-in-a-Fiber scheme using a periscope fiber for stable and compact alignment. We integrate droplet microfluidics with laser-induced fluorescence detection, demonstrating the generation of monodisperse droplets and achieving a limit of detection of fluorescein. Furthermore, we show the device's capability in detecting reverse-transcription loop-mediated isothermal amplification (RT-LAMP) products for COVID-19 diagnostics, highlighting its potential as a point-of-care droplet digital RT-LAMP platform.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Tyler Sano, Ravipa Losakul, Holger Schmidt
Summary: Integrated optofluidic devices, combining microfluidics and photonic structures, have gained high interest for rapid biosensor devices. Researchers demonstrated a polydimethylsiloxane-based device with two on-chip optofluidic laser cavities, enabling simultaneous detection of multiple fluorescent targets.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Analytical
Tyler Sano, Han Zhang, Ravipa Losakul, Holger Schmidt
Summary: Integrated biosensor platforms have become popular due to their ability to combine biosensor processes and functions into a single device, reducing response times. This study demonstrates a complete lab-on-chip system that integrates sample preparation, on-chip optofluidic dye laser, and optical detection, showcasing the potential for rapid and portable point-of-care devices.
Article
Optics
Yeonwoo Lee, Cheng-Hsun Lee, Sung-Yong Park
Summary: This study presents a new lens capability for three-dimensional (3D) focal control using an optofluidic system comprising of an n x n arrayed liquid prisms. The shape of the fluidic interface can be adjusted rapidly using the electrowetting effect to steer incoming rays at a tilted interface. Through simultaneous modulation of individual prisms in the arrayed system, 3D focal control can be achieved, allowing for spatial manipulation and convergence of incoming light rays. This innovative lens capability has potential applications in eye-movement tracking, autofocus for smartphone cameras, and solar tracking for photovoltaic systems.
Article
Chemistry, Analytical
Mahesh P. Bhat, Mahaveer Kurkuri, Dusan Losic, Madhuprasad Kigga, Tariq Altalhi
Summary: A PDMS microfluidic channel integrated with a UV-vis fibre-optic spectrometer and a new colorimetric probe was developed for sensitive and real-time quantitative measurements of fluoride ions (F). The device features an 'S' shaped microchannel acting as a microreactor to enhance the reaction between the colorimetric probe and F ions. This optofluidic device demonstrates high sensitivity and selectivity for F ions, outperforming conventional methods in detecting real samples.
ANALYTICA CHIMICA ACTA
(2021)
Article
Chemistry, Analytical
Zachary J. Walker, Tanner Wells, Ethan Belliston, Sage Romney, Seth B. Walker, Mohammad Julker Neyen Sampad, S. M. Saiduzzaman, Ravipa Losakul, Holger Schmidt, Aaron R. Hawkins
Summary: We present a method for fabricating and utilizing an optofluidic particle manipulator on a silicon chip. The chip features a solid-state membrane and hollow channels for fluid and particle transport, as well as light transmission and particle trapping using radiation pressure. The optofluidic platform includes ridge waveguides for directing light and intersecting liquid channels.
Review
Chemistry, Analytical
Mahmudur Rahman, Kazi Rafiqul Islam, Md. Rashedul Islam, Md. Jahirul Islam, Md. Rejvi Kaysir, Masuma Akter, Md. Arifur Rahman, S. M. Mahfuz Alam
Summary: Single-molecule techniques have revolutionized biological measurements by enabling the probing of individual molecules with high spatial and temporal resolution. Optical and electrical methods are commonly used for single-molecule detection, and advancements in fabrication techniques and optofluidics have paved the way for portable and chip-scale diagnostic tools. This review provides an overview of different single-molecule methods and manipulation techniques, with a focus on electrical control over single molecules.
Article
Chemistry, Analytical
Zachary J. Walker, Tanner Wells, Ethan Belliston, Seth B. Walker, Carson Zeller, Mohammad Julker Neyen Sampad, S. M. Saiduzzaman, Holger Schmidt, Aaron R. Hawkins
Summary: This article presents an optofluidic device that utilizes optical scattering and gradient forces to trap particles. Two different designs are compared and the second design is shown to have higher efficiency.
Article
Biochemical Research Methods
Pengming Song, Chengfei Guo, Shaowei Jiang, Tianbo Wang, Patrick Hu, Derek Hu, Zibang Zhang, Bin Feng, Guoan Zheng
Summary: This study presents a fully on-chip, lensless microscopy technique called optofluidic ptychography, which allows high-resolution quantitative complex imaging in a lab-on-a-chip setup. By integrating ptychographic microscopy into microfluidic devices, the technology can achieve high-resolution ptychographic reconstruction at video framerate and address a wide range of biomedical needs.
Article
Chemistry, Analytical
Joel G. Wright, Md Nafiz Amin, Holger Schmidt, Aaron R. Hawkins
Summary: Optofluidic flow-through biosensors are being developed for single particle detection, particularly for pathogen diagnosis. The sensitivity of the biosensor chip is affected by design parameters, illumination format, and flow configuration. Side-illumination combined with 3DHF produces the strongest and most consistent signal, while parabolic flow devices process sample volumes more quickly. Discussions also include practical matters of optical alignment that can impact design choices.
Review
Chemistry, Analytical
Irene Fernandez-Cuesta, Andreu Llobera, Maria Ramos-Payan
Summary: Optofluidics, a combination of microfluidics and photonics, has emerged as a forefront research area due to its superior properties. It enables handling of minute liquid samples at the microscale and offers high sensitivity and selectivity compared to other detection methods. The technology has advanced to allow selective detection of various analytes in complex liquid samples, paving the way for its applications in field and point-of-care settings.
ANALYTICA CHIMICA ACTA
(2022)
Article
Chemistry, Analytical
M. Jalal Uddin, Nabil H. Bhuiyan, Jun H. Hong, Joon S. Shim
Summary: A fully automated optofluidic device was developed for enzyme-linked immunosorbent assay using a smartphone-based optical platform. The platform successfully monitored liquid movement in the reaction chamber by measuring changes in light intensity, achieving a low detection limit for human cardiac biomarker detection.
ANALYTICAL CHEMISTRY
(2021)
Article
Chemistry, Analytical
Matthew Hamblin, Joel Wright, Holger Schmidt, Aaron R. Hawkins
Summary: Optofluidic biosensors have become an important medical tool for rapid and highly sensitive testing of small samples. This study compares alignment, power loss, and signal quality for different methods of top-down illumination using a validated model.
Article
Nanoscience & Nanotechnology
Ya Zhong, Haibo Yu, Yangdong Wen, Peilin Zhou, Hongji Guo, Wuhao Zou, Xiaofeng Lv, Lianqing Liu
Summary: This paper proposes a method for fabricating optofluidic tunable micro-lens arrays (MLAs) in polydimethylsiloxane (PDMS)-based microchannels via electrohydrodynamic jet (E-jet) printing. The MLAs with diameters ranging from 15 to 80 μm can be fabricated in microfluidic channels with widths of 200 and 300 μm using this method. By alternately using solutions with different refractive indices, the optofluidic microlenses demonstrate reversible modulation properties while preserving their morphology and refractive indices. The resulting optofluidic chip has a threefold tunable focal length, achieving an imaging depth of approximately 450 μm. This advantage is useful for observing microspheres and cells flowing in microfluidic systems, making the proposed optofluidic chip highly promising for cell counting and imaging applications.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Nanoscience & Nanotechnology
Deniz Mengu, Yifan Zhao, Anika Tabassum, Mona Jarrahi, Aydogan Ozcan
Summary: This study presents the use of diffractive optical networks to perform permutation operations with a large number of input-output connections. By using deep learning techniques, the capacity of the diffractive optical network to approximate permutation operations increases with the number of diffractive layers and trainable transmission elements in the system. The authors also addressed challenges related to physical alignment and output efficiency by designing misalignment tolerant diffractive designs. The proposed diffractive permutation networks have potential applications in security, image encryption, and data processing, and can serve as channel routing and interconnection panels in wireless networks.
Article
Chemistry, Multidisciplinary
Bijie Bai, Heming Wei, Xilin Yang, Tianyi Gan, Deniz Mengu, Mona Jarrahi, Aydogan Ozcan
Summary: This paper presents a diffractive optical network that performs data-class-specific transformations between the input and output fields-of-view (FOVs) using optical methods. The visual information of objects is encoded into the amplitude, phase, or intensity of the optical field at the input and processed by a data-class-specific diffractive network. The output patterns are optically encrypted using preassigned transformation matrices, and the original input images can be recovered by applying the correct decryption key.
ADVANCED MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Yuhang Li, Yi Luo, Bijie Bai, Aydogan Ozcan
Summary: Imaging through diffusive media is a challenging problem that typically requires digital computers for image reconstruction. In this study, we propose an alternative method using diffractive neural networks to see through random, unknown phase diffusers. Through detailed analysis, we observed a trade-off between image reconstruction fidelity and distortion reduction capability of the diffractive network. We also discovered that training the network with a variety of random diffusers and introducing misalignments improved its generalization performance.
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Gilbert Hangel, Barbara Schmitz-Abecassis, Nico Sollmann, Joana Pinto, Fatemehsadat Arzanforoosh, Frederik Barkhof, Thomas Booth, Marta Calvo-Imirizaldu, Guilherme Cassia, Marek Chmelik, Patricia Clement, Ece Ercan, Maria A. Fernandez-Seara, Julia Furtner, Elies Fuster-Garcia, Matthew Grech-Sollars, N. Tugay Guven, Gokce Hale Hatay, Golestan Karami, Vera C. Keil, Mina Kim, Johan A. F. Koekkoek, Simran Kukran, Laura Mancini, Ruben Emanuel Nechifor, Alpay Ozcan, Esin Ozturk-Isik, Senol Piskin, Kathleen M. Schmainda, Siri F. Svensson, Chih-Hsien Tseng, Saritha Unnikrishnan, Frans Vos, Esther Warnert, Moss Y. Zhao, Radim Jancalek, Teresa Nunes, Lydiane Hirschler, Marion Smits, Jan Petr, Kyrre E. Emblem
Summary: Preoperative clinical MRI protocols for gliomas still rely on conventional structural MRI, which does not provide information on tumor genotype and has limitations in the delineation of diffuse gliomas. The GliMR COST action aims to raise awareness about advanced MRI techniques in gliomas and their potential clinical translation. This review summarizes current methods, limitations, and applications of advanced MRI for the preoperative assessment of glioma, and evaluates the level of clinical validation of different techniques.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Lydiane Hirschler, Nico Sollmann, Barbara Schmitz-Abecassis, Joana Pinto, Fatemehsadat Arzanforoosh, Frederik Barkhof, Thomas Booth, Marta Calvo-Imirizaldu, Guilherme Cassia, Marek Chmelik, Patricia Clement, Ece Ercan, Maria A. Fernandez-Seara, Julia Furtner, Elies Fuster-Garcia, Matthew Grech-Sollars, Nazmiye Tugay Guven, Gokce Hale Hatay, Golestan Karami, Vera C. Keil, Mina Kim, Johan A. F. Koekkoek, Simran Kukran, Laura Mancini, Ruben Emanuel Nechifor, Alpay Oezcan, Esin Ozturk-Isik, Senol Piskin, Kathleen Schmainda, Siri F. Svensson, Chih-Hsien Tseng, Saritha Unnikrishnan, Frans Vos, Esther Warnert, Moss Y. Zhao, Radim Jancalek, Teresa Nunes, Kyrre E. Emblem, Marion Smits, Jan Petr, Gilbert Hangel
Summary: This article introduces the preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, which still rely on conventional structural MRI. However, this method lacks information on tumor genotype and has limitations in delineating diffuse gliomas. The GliMR COST action aims to raise awareness and discuss the clinical translation of advanced MRI techniques for gliomas.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Article
Multidisciplinary Sciences
Jingxi Li, Tianyi Gan, Yifan Zhao, Bijie Bai, Che-Yung Shen, Songyu Sun, Mona Jarrahi, Aydogan Ozcan
Summary: The first demonstration of unidirectional imagers is reported, presenting polarization-insensitive and broadband uni-directional imaging based on successive diffractive layers that are linear and isotropic. The diffractive unidirectional imager maintains its functionality over a large spectral band and works under broadband illumination. The diffractive unidirectional imaging using structured materials will have applications in security, defense, telecommunications, and privacy protection.
Article
Engineering, Biomedical
Tairan Liu, Yuzhu Li, Hatice Ceylan Koydemir, Yijie Zhang, Ethan Yang, Merve Eryilmaz, Hongda Wang, Jingxi Li, Bijie Bai, Guangdong Ma, Aydogan Ozcan
Summary: An automated plaque assay leveraging lens-free holographic imaging and deep learning rapidly and accurately detects the cell-lysing events caused by viral replication.
NATURE BIOMEDICAL ENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Yuhang Li, Jingxi Li, Yifan Zhao, Tianyi Gan, Jingtian Hu, Mona Jarrahi, Aydogan Ozcan
Summary: A universal polarization transformer is demonstrated that can synthesize various complex-valued polarization scattering matrices, providing a solution for controlled synthesis of optical fields with nonuniform polarization distributions.
ADVANCED MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Hanlong Chen, Luzhe Huang, Tairan Liu, Aydogan Ozcan
Summary: The application of deep learning techniques has significantly improved holographic imaging capabilities, with enhanced phase recovery and image reconstruction. This study introduces eFIN, a deep neural network that utilizes pixel super-resolution and image autofocusing for hologram reconstruction. Experimental results demonstrate the superior image quality and external generalization of eFIN, which achieves a wide autofocusing range and accurately predicts hologram axial distances. The network also enables 3x pixel super-resolution and improves the space-bandwidth product of reconstructed images by 9-fold.
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
(2023)
Review
Optics
Xurong Li, Jingxi Li, Yuhang Li, Aydogan Ozcan, Mona Jarrahi
Summary: This article reviews the development of terahertz imaging technologies and discusses different types of hardware and computational imaging algorithms. It explores opportunities for capturing various image data and briefly introduces the prospects and challenges for future high-throughput terahertz imaging systems.
LIGHT-SCIENCE & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Luzhe Huang, Hanlong Chen, Tairan Liu, Aydogan Ozcan
Summary: GedankenNet is a self-supervised learning model that achieves image reconstruction without the need for labelled or experimental training data, demonstrating superior generalization on hologram reconstruction tasks.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Automation & Control Systems
Che-Yung Shen, Jingxi Li, Deniz Mengu, Aydogan Ozcan
Summary: This study presents a diffractive processor for all-optical multispectral quantitative phase imaging of transparent objects. The processor encodes the phase profile of the input object at predetermined wavelengths into spatial intensity variations at the output plane using diffractive layers optimized through deep learning. Numerical simulations demonstrate its capability to perform quantitative phase imaging at multiple spectral bands and the generalization of the design is validated through tests on unseen objects. This diffractive multispectral processor offers a compact and power-efficient solution for high-throughput quantitative phase microscopy and spectroscopy due to its all-optical processing capability.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Article
Optics
Jingxi Li, Tianyi Gan, Bijie Bai, Yi Luo, Mona Jarrahi, Aydogan Ozcan
Summary: Large-scale linear operations are crucial for complex computational tasks, and optical computing offers advantages in terms of speed, parallelism, and scalability. The deep-learning-based design of a broadband diffractive neural network enables the performance of a large group of complex-valued linear transformations. By assigning different illumination wavelengths to each transformation, a single diffractive network can execute multiple linear transformations simultaneously or sequentially. This technology allows for the approximation of unique linear transforms with negligible errors, and the spectral multiplexing capability can be increased by increasing the number of diffractive neurons.
ADVANCED PHOTONICS
(2023)
Article
Automation & Control Systems
Md Sadman Sakib Rahman, Aydogan Ozcan
Summary: This study demonstrates for the first time a time-lapse image classification scheme using a diffractive network, improving classification accuracy and generalization performance by leveraging the lateral movements of the input objects and/or the diffractive network. Numerical exploration reveals a blind testing accuracy of 62.03% on the optical classification of objects from the CIFAR-10 dataset using time-lapse diffractive networks, achieving the highest inference accuracy so far. Time-lapse diffractive networks will be widely beneficial for spatiotemporal analysis of input signals using all-optical processors.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Article
Mathematical & Computational Biology
Michael John Fanous, Nir Pillar, Aydogan Ozcan
Summary: Traditional staining methods have drawbacks, while computational virtual staining using deep learning techniques has emerged as a powerful solution. Virtual staining can be combined with neural networks to correct microscopy aberrations and enhance resolution, significantly improving sample preparation and imaging in biomedical microscopy.
FRONTIERS IN BIOINFORMATICS
(2023)
