Lensfree Tomographic Imaging
- 技术优势
- Technology can be incorporated into microfluidicsMuch smaller form factor than traditional imaging techniquesLens-less technology
- 技术应用
- This technology could be used to generate tomography images of organelles, cells, cellular components, or small particles in static or flow based environments.
- 详细技术说明
- UCLA researchers led by Prof. Aydogan Ozcan have developed a new system for lens-free tomographic imaging. They have demonstrated for the first time in high resolution and large field of view a tomographic image utilizing a lens-free system on a microfluidic chip. This technology also allows for pixel super resolution techniques to be applied to optical tomographic imaging.
- *Abstract
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UCLA researchers in the Department of Electrical Engineering have developed a system for lens-free tomographic imaging.
- *Principal Investigation
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Name: Waheb Bishara
Department:
Name: Serhan Isikman
Department:
Name: Aydogan Ozcan
Department:
- 其他
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State Of Development
This technology has been used to visualize several biological and synthetic samples.
Background
Traditional light microscopy is a critical tool in medical imaging, diagnostics, and in research, however much of the technology remains fundamentally unchanged since their development (i.e. use of lenses and eyepiece/detector). In efforts to visualize increasingly smaller features and gain high resolution and contrast has resulted in significantly larger and more complex microscopes. With the advent of microfluidic (lab-on-a-chip) technology we have begun to be able to handle biological samples within miniaturized systems. However, we still rely on traditional light microscopes, which are several orders of magnitude larger, and have limited fields of view to image microfluidic devices. As a result there is a current clear need for miniaturized imaging platforms for microfluidic technologies.
Additional Technologies by these Inventors
- Ultra-Large Field-of-View Fluorescent Imaging Using a Flatbed Scanner
- Detection and Spatial Mapping of Mercury Contamination in Water Samples Using a Smart-Phone
- Automated Semen Analysis Using Holographic Imaging
- Tunable Vapor-Condensed Nano-Lenses
- 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
- Mobile Phone Based Fluorescence Multi-Well Plate Reader
- Phase Recovery And Holographic Image Reconstruction Using Neural Networks
- Air Quality Monitoring Using Mobile Microscopy And Machine Learning
Tech ID/UC Case
29202/2011-373-0
Related Cases
2011-373-0
- 国家/地区
- 美国
