CR图像自适应增强方法在头颈部的应用

数字CR检查在头颈部的应用克服了常规X线摄影一次曝光难以清晰显示骨与软组织位置关系的不足,使X线诊断更趋全面,并降低了X线辐射量.在成像过程中,由于各种不利因素的影响导致图像质量下降,要对其进行增强处理方能满足医生临床诊断的需要.一般的图像边缘细节增强算法未考虑人体不同部位的结构和密度特性.本文提出一种根据人体头颈部特点的自适应CR医学图像增强算法,利用该算法对头颈部图像进行边缘细节增强处理,并与线性反锐化掩模法处理后的图像进行比较,结果 表明该算法处理后的CR图像细节丰富,信噪比高,细节方差和背景方差之比(DV/BV)高,增强后的CR图像具有良好的视觉效果,是一种有效的适合头颈部CR医学放射图像的边缘细节增强方法.

Application of adaptive enhancement means in head and neck CR images

Digital CR of head and neck overcomes the disadvantage of regular X-ray radiography, which can not reveal bone and soft tissue position deficiency in one exposing, and reduces the X-ray radiation dose. Meanwhile, various factors decline the imaging quality, and images must be enhanced in order to meet demands of doctors clinical diagnosis. The general enhancement algorithms don't consider bodys structure difference and density characteristics. A new adaptive CR enhancement algorithms was proposed in this article, and head and neck images were processed with this method and compared with linear unsharp masking method. The results proved that the details of CR image enhanced were abundant and enhanced CR had good visual effect. SNR was high, as well as detail variance/background variance (DV/BV) indicating that this algorithms is suitable for head and neck CR medical image.