Abstract: Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multispectral imaging on a handheld 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 endpoint device. Cloud environments were designed to allow offloading of those problems by allowing endpoint devices (smartphones) to offload computationally hard tasks. For this end, we present a method where a handheld device based around a smartphone captures a multispectral dataset in a movie file format (mp4) and compare it to other image formats 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.
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