# A Systematic Overview of Recent Methods for Non-Contact Chronic Wound Analysis
## 9 Conclusions  
Chronic wounds as wounds that are not healing properly, dramatically affect national healthcare systems, so the need for quick and precise wound assessment is essential. Even though systems for the accurate segmentation and tissue classification of wounds exist they are not combined with accurate wound measurement or healing evaluation. Therefore, not a single system provides all the data needed for practical implementation in medical centers.  
Nevertheless, this overview showed that image analysis can handle wound segmentation and tissue classification tasks with some success. Therefore, with a combination of different methods, modifications of color spaces, or algorithms adjustment, some researchers achieved good performance and can be used for practical medical purposes under certain restrictions.  
The impact of any new developed method is measured by its accuracy, speed, and robustness. The novel method must be applicable for all kinds of wounds, types of skin, detect multiple wounds on different parts of the body, etc. Furthermore, the acquisition of wound images should be robust to uncontrolled lighting conditions and performed without user interference or be independent of physical accessories such as markers or rulers.  
With the development of high pixel smartphone and RGB-D cameras, an increase in computation power, and with the development of more accurate algorithms, wound image analysis has gradually taken precedence in the field of wound assessment. Furthermore, due to the improvements in automated wound analysis and global shortages of medical staff, the advent of artificial intelligence and robotic system can be foreseen. Moreover, the overall impact of chronic wounds in national healthcare systems is increasing; hence, the research papers in this field are expanding, and better and faster results can be expected.  
While the future is always uncertain, it is the opinion of the authors that the future development will see the realization of an AI driven automatic system for wound analysis comprised of robot manipulator with attached high precision industrial 3D camera and high resolution RGB camera. Such system would be able to autonomously detect wounds, record them from multiple views and create precise 3D models of the segmented wound surface. Furthermore, it would classify tissues on the surface and precisely measure the wound. Based on the data, a therapy would be prescribed and healing evaluation provided. Based on the available research, development of such a system is possible today with the right combination of hardware, tools and algorithms.  
In the future, wound analysis system should be a part of larger CDSS system where it will perform all the tasks necessary for wound assessment and, based on its results, CDSS could advise the clinician in order to provide better and faster wound treatment.  
Conceptualization, D.F.; research and original draft preparation, D.M.; review, editing and revised draft preparation, D.F. All authors have read and agreed to the published version of the manuscript.  
The paper is developed under project \"Methods for 3D reconstruction and analysis of chronic wounds\" and is funded by the Croatian Science Foundation under number UIP-2019-04-4889.  
The authors declare no conflict of interest.