基于局部特征分析的LDCT增强算法  

Novel Algorithm for Low-dose CT Image Enhancement Based on Local Feature Analysis

作　　者：张国栋[1,2] 颜培玉[2] 赵宏[1] 

机构地区：[1]东北大学软件中心,辽宁沈阳110004 [2]沈阳航空工业学院计算机学院,辽宁沈阳110136

出　　处：《小型微型计算机系统》2008年第12期2291-2295,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60441004,60671050)资助;沈阳市科学技术计划项目(1063297-1-00)资助;辽宁省教育厅科学研究计划项目(05L322)资助

摘　　要：针对CT影像灰度动态范围宽、对比度差的问题,提出一种基于局部特征分析的低剂量CT(Low-dose Computed Tomography,LDCT)影像增强算法.算法通过对影像全局和局部统计特征的分析,构造非线性变换函数,实现对活动子块所对应区域的局部动态范围拉伸.选用两组不同采集协议CT影像进行的对比实验表明,算法实现简捷,可有效增强影像中的细部解剖结构,并可较好地抑制LDCT影像中的线性伪影.算法已被用于肺癌计算机辅助诊断系统的预处理过程.In order to improve the intensity and contrast qualities of CT （Computed Tomography） images in clinic application, this paper proposed a fast and smart low-dose CT images contrast enhancement algorithm based on local feature analysis. The method based on creating active sub-blocks with analyzing the local static feature for each local region. Then, perform a local modified contrast stretching according to an adaptive transfer function within the image region corresponds with the sub-block. The experimental results of two sets CT images with different acquisition protocol （one with 200-250mA tube current, and another with 80mA） show that the proposed algorithm provides a flexible and efficient way for low-dose CT image enhancement, enhances the detail anatomic structure effectively, and constrains the linear artifacts in low-dose CT images preferably than general method. Now, the method is used as a pre-processing procedure in a Lung Cancer CAD system.

关 键 词：对比度增强 LDCT影像 局部统计特征 计算机辅助诊断 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]