A5038243196- Image Processing Techniques and Applications
- Advanced X-ray Imaging Techniques
- Digital Holography and Microscopy
- Antibiotics Pharmacokinetics and Efficacy
- Bacterial Identification and Susceptibility Testing
- Particle Accelerators and Free-Electron Lasers
- Photoacoustic and Ultrasonic Imaging
- Antibiotic Use and Resistance
- Astrophysical Phenomena and Observations
- Advanced Fluorescence Microscopy Techniques
University of Connecticut
2021-2022
Blu-ray drive is an engineering masterpiece that integrates disc rotation, pickup head translation, and three lasers in a compact portable format. Here we integrate blood-coated image sensor with modified for high-throughput cytometric analysis of various bio-specimens. In this device, samples are mounted on the rotating illuminated by built-in from head. The resulting coherent diffraction patterns then recorded sensor. rich spatial features blood-cell monolayer help down-modulate object...
The recent advent of whole slide imaging (WSI) systems has moved digital pathology closer to diagnostic applications and clinical practices. Integrating WSI with machine learning promises the growth this field in upcoming years. Here we report design implementation a handheld, colour-multiplexed, AI-powered ptychographic scanner for applications. This handheld is built using low-cost off-the-shelf components, including red, green, blue laser diodes sample illumination, modified stage...
Conventional ptychography translates an object through a localized probe beam to widen the field of view in real space. Fourier spectrum pupil aperture expand bandwidth reciprocal Here we report imaging modality, termed synthetic (SAP), get best both techniques. In SAP, illuminate stationary using extended plane wave and translate coded image sensor at far for data acquisition. The layer attached on modulates exit waves serves as effective ptychographic phase retrieval. translation process...
Structured illumination microscopy (SIM) enhances spatial resolution by projecting sinusoidal patterns with various orientations and lateral phase shifts. Here, we report a framework, termed DNN-SIM, powered deep neural network that learns the physical relationship between images different This approach captures one image per pattern orientation infers remaining phase-shifted network, reducing acquisition time to one-third of conventional 2D-SIM. We further extend DNN-SIM 3D applications...