Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches

Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due to unavailability of expert doctors. This problem generally affects older ageing people. So there is a need of better assessment facility to the remote people in telemedicine framework. Here we have proposed a CW tissue prediction and diagnosis under telemedicine framework to classify the tissue types using linear discriminant analysis (LDA). The proposed telemedicine based wound tissue prediction (TWTP) model is able to identify wound tissue and correctly predict the wound status with a good degree of accuracy. The overall performance of the proposed wound tissue prediction methodology has been measured based on ground truth images. The proposed methodology will assist the clinicians to take better decision towards diagnosis of CW in terms of quantitative information of three types of tissue composition at low-resource set-up.