Enhance The Contrast Of Skin Vascular Images Based On TiVi Imaging And Image Enhancement Algorithm

During clinical treatment,it is very important for the subsequent steps to locate blood vessels quickly and accurately,such as blood transportation,humor supply and so on.However,the success rate of puncture during intravenous injection depends mainly on the clinical experience of the medical staff recently.High failure rate of puncture during intravenous injection brings great pain to the patients,more importantly,it may delay the rescue time if the puncture failure occurs in the first aid,which would affect the result of treatment.Therefore,obtain high contrast skin blood vessels images reliably and in real time is of great significance for clinical diagnosis.The work of this thesis is focused on how to improve the contrast of skin blood vessel images,the contents and results were as follows:Established an imaging system of Tissue Viability,and combined it with Tissue Optical Clearing technology,to obtain the images of the subcutaneous blood vessels of the mice and the human body in vivo.the improvement in quality of the images of subcutaneous blood vessels before and after the treatment of TOC technology was quantitatively analyzed.The results showed that TOC technology could significantly improve the image quality of subcutaneous vessels in mice,but it is not so effective in human subcutaneous vessels.In order to improve the contrast of subcutaneous vascular images in vivo,we used an algorithm called adaptive unsharp masking to deal with the subcutaneous blood vessel images obtained before.The improvement in quality of the images of subcutaneous vessels before and after the treatment of the image contrast enhancement algorithm was quantitatively analyzed.The results show that the adaptive unsharp masking algorithm can significantly improve the contrast of subcutaneous vascular images in vivo.However,the principle of the algorithm is a little bit complex,which leads to complex computational cost and time consume.Further,we used an adaptive image contrast enhancement algorithm based on local standard deviation to deal with the acquired blood vessel image.The improvement in quality of the images of subcutaneous vessels before and after the treatment of the image contrast enhancement algorithm was quantitatively analyzed.The results show that the adaptive image contrast enhancement algorithm based on local standard deviation can significantly enhance the contrast of subcutaneous vascular images in vivo.Then,we extend the application range of the algorithm from gray image to color image processing,and apply the extended algorithm to the human subcutaneous blood vessel image.The result shows that the proposed algorithm works very well in color image of subcutaneous blood vessel in vivo.