Mobile Phone Based Fluorescence Multi-Well Plate Reader

Cost-effectiveFast fiber optic bundle based fluorescence microplate readerIntegrated onto the optical camera interface of a mobile phoneField-portableCost-effectiveMobile phone based readout platform Compatible with any fluorescence based assay that can be run in a 96-well microplate format

UCLA researchers working with Dr. Aydogan Ozcan have developed a fluorescence microplate reader integrated onto the optical camera interface of a mobile phone. This device uses a cost-effective fiber optic bundle to create the microplate reader.

Background

Key challenges with point-of-care (POC) tests include achieving a low cost, portable form and stable readout. Additionally, POC tests need to retain the same robust standards of benchtop and lab-based tests.

Additional Technologies by these Inventors

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• Single Molecule Imaging and Sizing of DNA on a Cell Phone
• Rapid, Portable And Cost-Effective Yeast Cell Viability And Concentration Analysis Using Lensfree On-Chip Microscopy And Machine Learning
• Wide-Field Imaging Of Birefringent Crystals In Synovial Fluid Using Lens-Free Polarized Microscopy For Crystal Arthropathy Diagnosis
• Quantitative Fluorescence Sensing Through Highly Autofluorescent And Scattering Media Using Cost-Effective Mobile Microscopy
• Demosaiced Pixel Super-Resolution For Multiplexed Holographic Color Imaging
• Microscopic Color Imaging And Calibration
• Pixel Super-Resolution Using Wavelength Scanning
• High-Throughput And Label-Free Single Nanoparticle Sizing Based On Time-Resolved On-Chip Microscopy
• Fluorescent Imaging Of Single Nano-Particles And Viruses On A Smart-Phone
• Holographic Opto-Fluidic Microscopy
• Lensfree Wide-Field Fluorescent Imaging On A Chip Using Compressive Decoding
• Revolutionizing Micro-Array Technologies: A Microscopy Method and System Incorporating Nanofeatures
• Sparsity-Based Multi-Height Phase Recovery In Holographic Microscopy
• Computational Out-Of-Focus Imaging Increases The Space-Bandwidth Product In Lens-Based Coherent Microscopy
• Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning
• Deep Learning Microscopy
• Phase Recovery And Holographic Image Reconstruction Using Neural Networks
• Lensfree Tomographic Imaging
• Air Quality Monitoring Using Mobile Microscopy And Machine Learning

Tech ID/UC Case

28975/2017-440-0

Related Cases

2017-440-0

美国

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