Real time wound segmentation/management using image processing on handheld devices

Issue title: Selected Papers from ICCMEH2014

Guest editors: Raghuvir Pai

Article type: Research Article

Authors: Gupta, Abhiraj

Affiliations: CSE Department, Manipal Institute of Technology, Manipal, India. E-mail: abhirajgupta.mit@gmail.com

Abstract: Diffusion of mobile technology presents numerous opportunities to bend healthcare cost curve. Chronic wounds are a global, ongoing health challenge that afflicts a large number of people. Effective diagnosis and treatment of the wounds relies largely on a precise identification and measurement of the wounded tissue; however, in current clinical process, wound evaluation is based on subjective visual inspection and manual measurements which are often inaccurate. Given the cost and inconvenience of regular visits to wound clinics and for providing real time aid/care to remote and rural areas smart phone app named, Wound Vision which tracks/identifies the wound size, healing/management process based on images captured/processed within a smart phone is designed. Therefore this automated mobile-based system for fast and accurate segmentation and identification of wounds is desirable, both from the standpoint of improving health outcomes in chronic wound care, and in making clinical practice efficient and cost-effective for people in remote areas and cities. Satisfactory results of this real time mobile system suggest a promising tool to assist in the field of clinical wound evaluation. The simplicity of the algorithm/framework used suggests that it is a valuable tool in clinical wound evaluation. Future work will incorporate additional features (wound Tissue analysis-necrotic, fibrin & granulation tissue) for assessing the wound healing process in order to completely replace clinical praxis. A working model of the application has been made and further optimizations are in progress.

Keywords: Wound segmentation & detection, healing rate, OpenCV, android

DOI: 10.3233/JCM-170706

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 17, no. 2, pp. 321-329, 2017