Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.
Amir S. Bernat, Frank J. Bolton, Reuven Weiser, and David Levitz, "Cloud-based processing of multi-spectral imaging data," Proc. SPIE 10055, Optics and Biophotonics in Low-Resource Settings III, 1005505 (Presented at SPIE BiOS: January 28, 2017; Published: 3 March 2017); https://doi.org/10.1117/12.2252189.
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