Comparison of histogram enhancement approaches to MRI image based on interactive data language / 中国组织工程研究

ABSTRACT

AIM:To compare the effects of different histogram enhancement algorithms on improving the quality of MRI image.METHODS:Three processing algorithms,including histogram equalization,adaptive histogram equalization and histogram specification,were applied to enhance a MRI cervical spine T2-weighted image based on programming software interactive data language.The capability of representation of details in dark area and the level of noise were evaluated by means of peak signal to noise ratio and image information entropy.RESULTS:Histogram equalization cannot enhance the details in dark region obviously,but decline the contrast of whole image;adaptive histogram equalization can improve details but enlarge noise and engender shadow at edges simultaneously;histogram specification can choose the type of histogram function to match;it reveals the details in dark area sufficiently,and there is the lowest level of noise among these three algorithms.CONCLUSION:MRI cervical spine T2-weighted image processing with different algorithms of histogram enhancement,histogram specification is more outstanding than histogram equalization and adaptive histogram equalization in the representation of details and the low-level of noise.