Wound analysis using image processing techniques

Developments in the fields of technology and engineering enable the use of new technologies in the health sector. In this context, the applications of image processing techniques in healthcare are increasing. The aim of this thesis is to monitor the healing process of wounds with image processing techniques and to make predictions about this process. After treatment of open wounds, monitoring the condition and healing process of the wound is vital for the effectiveness of the treatment and the patient's response to the treatment. The effects of the treatment should be continued when it shows signs of improvement, otherwise it should be changed or the causes should be investigated. With traditional methods, monitoring of the process is limited to visual observation by healthcare professionals and feedback from the patient. However, compared to observations made with the human eye, computer-aided image analysis is much more efficient and faster. Especially monitoring changes in short time intervals is facilitated by this method. Thus, personal error margins can be reduced, the process can be monitored objectively and precisely, support is provided to healthcare professionals and the workload is alleviated. In this thesis, image processing techniques and regression models were applied using open source mouse wound images, and the healing processes of the wounds were transferred to the computer environment and predictions were created.