To be able to use the latest diagnostic algorithms and still have fast acting automated diagnostic system, we propose using distributed cloud-based system. In that system, diagnostic device is used only for image acquisition under special multispectral illumination (405nm, 535nm, 660nm and 950nm). Obtained skin imaged are sent further to cloud system for analysis and diagnostic results visualization. By means of proposed approach, images could be processed by using the same Matlab  algorithms  that skin cancer research team is using. That will eliminate the need of adopting each algorithm to a specific architecture of diagnostic device. Moreover, the proposed system keeps relation between multiple skin analysis from each patient and could be used to track skin lesions changes in time. Proposed cloud system has architecture that allows fast scaling according to real-time requirements. Proposed system uses central load balancing server, that accepts diagnostic requests and sends image processing request to less loaded Matlab processing station. In case of high load, balancing server can launch an additional processing station. Therefore, it brings main cloud system advantages – efficient resource usage and fast adopting to current needs by increasing processing power. The cloud system is using Vagrant virtual machine management tool that allows easily recreating proposed cloud system as local-private cloud in situations where diagnostic results require high level of security.
The system is being tested in ongoing European project by the biophotonic research team and medical personal. The results of clinical testing will follow after completing first stage of clinical tests.
This work has been supported by European Regional Development Fund project ‘Portable Device for Non-Contact Early Diagnostics of Skin Cancer’ under grant agreement # 184.108.40.206/16/A/197.