Research And Implementation Of The Method For Evaluating The Treatment Effect Of Port-wine Stains

The evaluation of the treatment effect of port-wine stains is very important to accurately grasp the clinical treatment process. As we all know, the clinical evaluation which is easily affected by subjectivity relies on the judgment of doctor’s qualitative judgments, and different doctors may have quite different assessment results for the same case. Actually it is very significant for us to find a unified objective evaluation method. The assessment of port-wine stains image by computer analysis is an objective economic method in many kinds of the existing methods.The main feature of the skin treatment of port-wine stains is the change of lesion skin in color and size. That is to say, we need to know the theory and process of color space and image segmentation,according the feature of port-wine stains to choose appropriate color space and segmentation algorithm.This paper has analyzed the assessment method of the port-wine stains treatment effect.That is an objective evaluation method using the numerical image treatment area, including the image preprocessing, the detection of the color change and area change in the lesion area. Firstly, the preprocessing can help us reduce the external influence during the process of image capture. Secondly, the color change assessment of port-wine stains by using L*a*b* spatial assessment gives us a color change detection of the treatment. Then, Otsu algorithm could extract the lesion area and detect area change. Lastly, the combination of color change and area change in lesion area before and after treatment help us evaluate the treatment effect of port-wine stains.This article has designed a software evaluation system for port-wine stains treatment effect rely on the evaluation method, provided the system structure and design process of key module, fully achieved the evaluation method and the numerical characteristics of the treatment effect. This design selected 20 pictures of patients randomly to compare the evaluation result of the software evaluation system and the five clinicians based on their experience. By statistical analyzing and comparing the results, they are highly correlated, That is to say the software evaluation system result correspond to the clinical prediction, and even more objective and accurate.