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Proceedings Paper

Cloud infrastructure for skin cancer scalable detection system
Author(s): Pavels Osipovs; Dmitrijs Bliznuks; Alexey Lihachev
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Paper Abstract

Skin cancer diagnostics is one of the medical areas where early diagnostic allows achieving patients’ high survival rate. Typically, skin cancer diagnostic is performed by dermatologist, since the amount of such specialists is limited, mortality rate is high [1]. By creating the low cost and easy to use diagnostic device, it is possible to bring skin cancer diagnostic to primary care physicians and allow to check much more persons and diagnose skin cancer on the early stages. There are several existing devices, that provide skin cancer diagnostics [2]. Most of them process the skin images locally and have limited diagnostic capabilities; some of them send images to dermatologists for manual analysis to achieve higher diagnostic quality. Therefore, there is a lack of diagnostic quality or response time.

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 [3] algorithms [4] 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 # 1.1.1.1/16/A/197.

Paper Details

Date Published: 24 May 2018
PDF: 11 pages
Proc. SPIE 10679, Optics, Photonics, and Digital Technologies for Imaging Applications V, 1067905 (24 May 2018); doi: 10.1117/12.2306674
Show Author Affiliations
Pavels Osipovs, Riga Technical Univ. (Latvia)
Dmitrijs Bliznuks, Riga Technical Univ. (Latvia)
Alexey Lihachev, Univ. of Latvia (Latvia)


Published in SPIE Proceedings Vol. 10679:
Optics, Photonics, and Digital Technologies for Imaging Applications V
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal, Editor(s)

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