数字CR医学图像自适应增强算法研究

The research of digital CR medicine image adaptive enhancement algorithm

数字CR(Computed Radiography)医学放射图像以其高灰阶分辨率、强大的计算机图像后处理功能、小辐射剂量、无胶片诊断、异地会诊等优势,已成为医学成像技术新的热点。然而在成像过程中,由于人体结构和组织的复杂性以及成像系统中的X线散射、电器噪声等各种不利因素的影响导致图像质量的下降,主要表现为细节模糊、对比度差,要对其进行增强处理以改善其视觉质量,便于医生更准确地诊断。而目前通用的CR图像增强方法对比度和噪声增强过度,丢失细节,为此提出一种基于邻域标准差与均值之比自适应增强算法。算法能根据CR图像的邻域标准差与均值之比来调节增强程度的加权因数k,从而自适应的增强CR图像的边缘细节。实验证明,该算法处理后的CR图像细节丰富,信噪比高,具有良好的视觉效果,是一种有效的适合CR医学放射图像的自适应增强算法。

Digital CR medicine radiation image is in doctor＇s favor and has became medicine imaging technology new hot spot because of its high gray contrast、powerful computer disposal function、little radiation dosage、non-film diagnosis、different area consultation.But degradation of digital X-ray medical image such as low contrast and blurring during radiographic imaging, caused by complexity of body tissue and effects of X-ray scattering and electrical noise etc., can worsen the results of analysis and diagnosis.So it is usually needed that CR medicine image is enhanced to improve its vision quality, and easy to doctor ＇s more accurate diagnosis.The general enhancement algorithms over enhancing the contrast and lose image details, aiming at the defects, an enhancement algorithm for CR image is proposed based on the ratio of deviation to mean of domain.The arithmetic enhance CR image edge details by adjusting factor K based on the ratio of deviation to mean of domain of CR image.Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect, the adaptive enhancement method is fit for CR medicine image.