Search Results - yair+rivenson

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Deep Learning Achieves Super-Resolution in Fluorescence Microscopy (Case No. 2018-739)
Summary: UCLA researchers in the Department of Electrical Engineering have developed a novel high-speed and non-iterative approach of achieving super-resolution in fluorescence microscopy using deep learning. Background: Super-resolution microscopy such as structured illumination microscopy allows visualization of intricate details of cellular features...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Yair Rivenson, Hongda Wang
Keywords(s):  
Category(s): Electrical, Electrical > Imaging, Optics & Photonics, Optics & Photonics > Microscopy, Optics & Photonics > Holography
Deep Learning-Based 3D Imaging of Fluorescent Samples from 2D Image (Case No. 2019-521)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a deep learning-based approach termed Deep-Z that enables 3D imaging of fluorescent samples using a single 2D image, without mechanical scanning, additional hardware, or a trade-off resolution or speed. Background: Three-dimensional (3D) fluorescence...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Yair Rivenson, Yichen Wu
Keywords(s): Image Processing, Imaging, Medical Imaging, Microscope, Microscopy And Imaging
Category(s): Electrical, Electrical > Imaging, Life Science Research Tools > Microscopy And Imaging
2022-140 Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue Using Deep Learning
SUMMARY: UCLA researchers in the Departments of Bioengineering and Electrical and Computer Engineering have developed a deep learning-based algorithm that can detect and quantify the breast cancer marker human epidermal growth factor receptor 2 (HER2) in microscopic images without the need for time-consuming immunohistochemical staining (IHC). BACKGROUND:...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Yair Rivenson, Bijie Bai, Hongda Wang
Keywords(s): Artifical Intelligence (Machine Learning, Data Mining), Biomarker, Bladder Cancer, Breast Cancer, Cancer, Cancer Immunotherapy, Computer Aided Learning, Diagnostic Markers & Platforms, Diagnostic Test, Fluorescence, Fluorescent Labelling, HER2/Neu, Histology, Immune System, Immunohistochemistry, Life Science Research Tools, Machine Learning, Optics, Research Methods, Unsupervised Learning
Category(s): Life Science Research Tools, Life Science Research Tools > Research Methods, Diagnostic Markers, Diagnostic Markers > Immunology, Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > Fluorescence, Software & Algorithms > Artificial Intelligence & Machine Learning, Optics & Photonics
2020-487 Early-Detection and Classification of Live Bacteria Using Time-Lapse Coherent Imaging and Deep Learning
Summary: Researchers from UCLA’s Electrical and Computer Engineering and Bioengineering Departments have invented a novel automated system that quickly detects and classifies colonies of live bacteria in water by using deep neural networks to analyze holographic images. Background: Early identification of pathogenic bacteria in food, water,...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Yair Rivenson, Hongda Wang, Hatice Ceylan Koydemir, Yunzhe Qiu
Keywords(s): Diagnostic Platform Technologies (E.G. Microfluidics), Hospital Systems And Devices, Imaging, Instrumentation & Analysis, Life Science Research Tools, Microscopy And Imaging
Category(s): Electrical > Instrumentation, Electrical > Imaging, Software & Algorithms, Diagnostic Markers, Software & Algorithms > Artificial Intelligence & Machine Learning
2021-359 Seeing Through Random Diffusers Without a Computer
Summary: UCLA researchers in the department of Electrical and Computer Engineering have developed an all optics-based system that can perform image reconstruction at the speed of light for images distorted by light scattering and diffusion. Background: Imaging is an essential technique for everything from biomedical optics and atmospheric physics...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Yi Luo, Ege Cetintas, Yair Rivenson
Keywords(s): Automation, Computer Vision, Digital Electronics, Electronics & Semiconductors, Optics, Photonics, Remote Sensing, Robotics, Signal Reconstruction, Turbines
Category(s): Electrical, Electrical > Electronics & Semiconductors, Electrical > Imaging, Mechanical, Mechanical > Instrumentation, Mechanical > Robotics, Optics & Photonics
2021-344 Biopsy-Free In Vivo Virtual Histology of Skin Using Deep Learning
Summary: UCLA researchers in the Departments of Electrical and Computer Engineering & Bioengineering have developed a non-invasive, biopsy-free technique for in vivo virtual histology of skin cancer using deep learning. Background: Tissue biopsies have often been used to diagnose skin cancers in patients. These procedures are generally cumbersome...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Jingxi Li, Yair Rivenson, Xiaoran Zhang, Philip Scumpia, Jason Garfinkel, Gennady Rubinstein
Keywords(s): Artificial Intelligence, Biopsy, Cancer, Confocal Microscopy, Diagnostic Test, Histology, Image Resolution, Invasiveness Of Surgical Procedures, Melanoma, Optics, Skin, Software, Tissue (Biology), Tumor
Category(s): Software & Algorithms, Software & Algorithms > Image Processing, Life Science Research Tools, Life Science Research Tools > Microscopy And Imaging, Electrical > Imaging, Medical Devices > Medical Imaging, Optics & Photonics
2021-104 Deep Learning-Based Spectral Reconstruction Using a Scalable Plasmonic Encoder
Summary: UCLA researchers in the department of Electrical and Computer Engineering have developed a deep learning-based device that uses a scalable plasmonic encoder to spectrally reconstruct a variety of complex mixed data from analytical chemistry to astronomy with high spectral resolution. Background: Optical sensors have become paramount in...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Calvin Brown, Artem Goncharov, Zachary Ballard, Yair Rivenson
Keywords(s): Artificial Intelligence, Image Processing, Instrumentation & Analysis, Machine Learning, Optics, Sensors
Category(s): Software & Algorithms > Image Processing, Software & Algorithms > Artificial Intelligence & Machine Learning, Optics & Photonics
2021-072 Ensemble Learning of Diffractive Optical Networks
SUMMARYUCLA researchers in the Department of Electrical and Computer Engineering have improved the statistical inference performance of diffractive optical networks for artificial intelligence-related applications.BACKGROUNDOptical computing platforms are having renewed interest in artificial intelligence-related applications. Due to their high speed,...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, MD Sadman Sakib Rahman, Jingxi Li, Yair Rivenson, Deniz Mengu
Keywords(s):  
Category(s): Software & Algorithms > Artificial Intelligence & Machine Learning, Optics & Photonics
2021-103 Scale-, Shift- and Rotation-Invariant Diffractive Optical Networks
SUMMARYUCLA researchers in the Department of Electrical and Computer Engineering developed a diffractive optical network training strategy that guides the design toward a scale-, shift- and rotation-invariant solution.BACKGROUNDOptical neural networks have gained popularity in the recent years over their electronic counterparts due to their power efficiency,...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Deniz Mengu, Yair Rivenson
Keywords(s):  
Category(s): Software & Algorithms > Image Processing, Software & Algorithms > Artificial Intelligence & Machine Learning, Optics & Photonics
2020-932 Terahertz Pulse Shaping Using Diffractive Legos
SUMMARYUCLA researchers in the Department of Electrical and Computer Engineering have developed an all-optical diffractive network. This learning-based diffractive pulse engineering framework utilizes deep learning and wave-optics to design an arbitrarily shaped broadband pulse into a desired waveform across a broad bandwidth and high spectral resolution.BACKGROUNDMachine...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Deniz Mengu, Yair Rivenson, Muhammed Veli
Keywords(s):  
Category(s): Software & Algorithms > Communication & Networking, Software & Algorithms > Artificial Intelligence & Machine Learning
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