354 citations · 2.8k across the 40 of their papers we have counts for
40 papers
All-optical image denoising using a diffractive visual processor
Cagatay Isıl, Tianyi Gan, F. Onuralp Ardic +9
Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers,…
Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network
Che-Yung Shen, Jingxi Li, Deniz Mengu +1
As a label-free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials…
Cycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems
Luzhe Huang, Jianing Li, Xiaofu Ding +3
Uncertainty estimation is critical for numerous applications of deep neural networks and draws growing attention from researchers. Here, we demonstrate an uncertainty quantificatio…
Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array
Dehui Zhang, Dong Xu, Yuhang Li +14
Nonlinear optical processing of ambient natural light is highly desired in computational imaging and sensing applications. A strong optical nonlinear response that can work under w…
Learning Diffractive Optical Communication Around Arbitrary Opaque Occlusions
Md Sadman Sakib Rahman, Tianyi Gan, Emir Arda Deger +3
Free-space optical systems are emerging for high data rate communication and transfer of information in indoor and outdoor settings. However, free-space optical communication becom…
Universal Polarization Transformations: Spatial programming of polarization scattering matrices using a deep learning-designed diffractive polarization transformer
Yuhang Li, Jingxi Li, Yifan Zhao +4
We demonstrate universal polarization transformers based on an engineered diffractive volume, which can synthesize a large set of arbitrarily-selected, complex-valued polarization…
Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding
Yuhang Li, Tianyi Gan, Bijie Bai +3
Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due…
Universal Linear Intensity Transformations Using Spatially-Incoherent Diffractive Processors
Md Sadman Sakib Rahman, Xilin Yang, Jingxi Li +2
Under spatially-coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between…
Rapid Sensing of Hidden Objects and Defects using a Single-Pixel Diffractive Terahertz Processor
Jingxi Li, Xurong Li, Nezih T. Yardimci +6
Terahertz waves offer numerous advantages for the nondestructive detection of hidden objects/defects in materials, as they can penetrate through most optically-opaque materials. Ho…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Deep learning-enabled multiplexed point-of-care sensor using a paper-based fluorescence vertical flow assay
Artem Goncharov, Hyou-Arm Joung, Rajesh Ghosh +8
We demonstrate multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury. This point-of-care se…
Quantitative phase imaging (QPI) through random diffusers using a diffractive optical network
Yuhang Li, Yi Luo, Deniz Mengu +2
Quantitative phase imaging (QPI) is a label-free computational imaging technique used in various fields, including biology and medical research. Modern QPI systems typically rely o…
eFIN: Enhanced Fourier Imager Network for generalizable autofocusing and pixel super-resolution in holographic imaging
Hanlong Chen, Luzhe Huang, Tairan Liu +1
The application of deep learning techniques has greatly enhanced holographic imaging capabilities, leading to improved phase recovery and image reconstruction. Here, we introduce a…
Data class-specific all-optical transformations and encryption
Bijie Bai, Heming Wei, Xilin Yang +2
Diffractive optical networks provide rich opportunities for visual computing tasks since the spatial information of a scene can be directly accessed by a diffractive processor with…
Snapshot Multispectral Imaging Using a Diffractive Optical Network
Deniz Mengu, Anika Tabassum, Mona Jarrahi +1
Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network…
Unidirectional Imaging using Deep Learning-Designed Materials
Jingxi Li, Tianyi Gan, Yifan Zhao +5
A unidirectional imager would only permit image formation along one direction, from an input field-of-view (FOV) A to an output FOV B, and in the reverse path, the image formation…
Deep Learning-enabled Virtual Histological Staining of Biological Samples
Bijie Bai, Xilin Yang, Yuzhu Li +3
Histological staining is the gold standard for tissue examination in clinical pathology and life-science research, which visualizes the tissue and cellular structures using chromat…
Self-supervised learning of hologram reconstruction using physics consistency
Luzhe Huang, Hanlong Chen, Tairan Liu +1
The past decade has witnessed transformative applications of deep learning in various computational imaging, sensing and microscopy tasks. Due to the supervised learning schemes em…
Virtual impactor-based label-free bio-aerosol detection using holography and deep learning
Yi Luo, Yijie Zhang, Tairan Liu +3
Exposure to bio-aerosols such as mold spores and pollen can lead to adverse health effects. There is a need for a portable and cost-effective device for long-term monitoring and qu…
Time-lapse image classification using a diffractive neural network
Md Sadman Sakib Rahman, Aydogan Ozcan
Diffractive deep neural networks (D2NNs) define an all-optical computing framework comprised of spatially engineered passive surfaces that collectively process optical input inform…
Massively Parallel Universal Linear Transformations using a Wavelength-Multiplexed Diffractive Optical Network
Jingxi Li, Bijie Bai, Yi Luo +1
We report deep learning-based design of a massively parallel broadband diffractive neural network for all-optically performing a large group of arbitrarily-selected, complex-valued…
Virtual stain transfer in histology via cascaded deep neural networks
Xilin Yang, Bijie Bai, Yijie Zhang +4
Pathological diagnosis relies on the visual inspection of histologically stained thin tissue specimens, where different types of stains are applied to bring contrast to and highlig…
Virtual staining of defocused autofluorescence images of unlabeled tissue using deep neural networks
Yijie Zhang, Luzhe Huang, Tairan Liu +5
Deep learning-based virtual staining was developed to introduce image contrast to label-free tissue sections, digitally matching the histological staining, which is time-consuming,…
Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning
Tairan Liu, Yuzhu Li, Hatice Ceylan Koydemir +8
We present a rapid and stain-free quantitative viral plaque assay using lensfree holographic imaging and deep learning. This cost-effective, compact, and automated device significa…