Wunderkint

Description: 

The correct identification of the cause of chronic wounds and the subsequent adequate treatment are decisive for the success of the therapy. Photographic wound documentation is already used by physicians, wound managers and nursing services to estimate the success of the therapy. However, the evaluation of the photos is usually subjective and is carried out by the respective therapist. For an objective evaluation, it is necessary to measure the wound area and estimate the wound depth. Computer-aided recognition and segmentation of the wound area offers the possibility of a simple and objective monitoring of the success of the therapy and is moreover available to the patient at any time. The automated processing of images of chronic wounds by means of machine learning and neural networks can help to diagnose rare and difficult-to-treat causes of chronic wounds more easily and accurately. Within the scope of this project, a software-based application will be developed to support patient care, improve therapy success and reduce therapy costs in the long term.

Project management:

- SE Group:  Vanessa Borst
- UKW Würzburg: Prof. Dr. med. Astrid Schmieder, Dr. med. Tassilo Dege
 

Project Start: 01.10.2021