Presentation + Paper
22 April 2020 Portable flow device using Fourier ptychography microscopy and deep learning for detection in biosignatures
Author Affiliations +
Abstract
A proof-of-concept, compact, portable Fourier Ptychographic Microscope (FPM) to perform wide field-of-view, high spatial resolution imaging (<1 μm) for biosignature motility in liquid samples, is presented. The FPM has the potential method to be developed as a space-based payload for future landers destined to the Ocean Worlds. A portable FPM using an existing Fourier ptychography (FP) algorithm adapted for reconstruction is demonstrated. A NVIDIA Jetson Nano board and camera combined with FP, is used to computationally reconstruct sub-micron resolution images. Additionally, deep learning was employed to perform inferencing prediction which enables the on-edge FPM device.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thanh Nguyen, Shahid Aslam, Dina Bower, Jennifer L. Eigenbrode, Nicolas Gorius, Tilak Hewagama, Laddawan Miko, and George Nehmetallah "Portable flow device using Fourier ptychography microscopy and deep learning for detection in biosignatures", Proc. SPIE 11401, Real-Time Image Processing and Deep Learning 2020, 114010H (22 April 2020); https://doi.org/10.1117/12.2557316
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KEYWORDS
Data modeling

Image resolution

Microscopes

Reconstruction algorithms

Light emitting diodes

Liquids

Microscopy

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