Journal of Computer Applications ›› 2013, Vol. 33 ›› Issue (06): 1727-1731.DOI: 10.3724/SP.J.1087.2013.01727

• Network and distributed techno • Previous Articles     Next Articles

Medical images fusion of nonsubsampled Contourlet transform and regional feature

LI Chao1,LI Guangyao1,TAN Yunlan1,2,XU Xianglong1   

  1. 1. College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
    2. College of Electronics and Information Engineering, Jinggangshan University, Jinggangshan Jiangxi 343009, China
  • Received:2012-12-19 Revised:2013-01-25 Online:2013-06-01 Published:2013-06-05
  • Contact: LI Chao

基于非下采样Contourlet变换和区域特征的医学图像融合

李超1,李光耀1,谭云兰1,2,徐祥龙1   

  1. 1. 同济大学 电子与信息工程学院,上海 201804
    2. 井冈山大学 电子与信息工程学院,江西 井冈山 343009
  • 通讯作者: 李超
  • 作者简介:李超(1979-),男,安徽合肥人,讲师,博士研究生,主要研究方向:虚拟现实、图形图像处理;李光耀(1965-),男,安徽安庆人,教授,博士生导师,主要研究方向:大规模城市建模与仿真、图形图像处理;谭云兰(1972-),女,江西新干人,副教授,博士研究生,主要研究方向:图像处理;徐祥龙(1988-),男,山东临沂人,硕士研究生,主要研究方向:地形建模与仿真、图形图像处理。
  • 基金资助:

    国家863计划重点项目(2010AA122200)

Abstract: With reference to the properties of multiscale and shift invariance of nonsubsampled Contourlet transform, and concerning the characteristics of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images, a medical images fusion method was proposed.The proposed method fused the low frequency subband and high frequency subband of these medical images separately by the regional feature strategy. The paper introduced the judgment criteria of images fusion and expatiated on the principle and implementation of Nonsubsampled Contourlet Transform (NSCT). And this gave the subjective judgment and numeric measurement of the fusion images based on visual effect and information indexes. To evaluate the performance of the proposed algorithm, the authors compared the results with those of the algorithms, such as wavelet transform and Contourlet transform. The CT and MRI images simulation results of mandibular system indicate that the proposed method outperforms the others in terms of both visual quality and objective evaluation criteria, while it can integrate and maintain much more effective and detailed information as well.

Key words: nonsubsampled Contourlet transform, regional feature, medical image fusion, wavelet transform

摘要: 针对非下采样Contourlet变换具有多尺度分析及平移不变的性质,结合计算机断层成像(CT)和核磁共振(MRI)医学图像各自的成像特性,提出了基于非下采样Contourlet变换和区域特征策略来对低频、高频子带进行融合的医学图像融合方法;介绍了图像融合的评价标准,阐述了非下采样Contourlet变换的原理及实现;从视觉效果和客观数据指标方面对融合图像进行主观评判和数值评价。下颌骨系统CT和MRI图像的融合实验结果表明,该方法相对于小波变换和Contourlet变换方法,可有效综合这两种断层图像的有效信息和细节信息,融合后图像具有更优的视觉质量和量化指标。

关键词: 非下采样Contourlet变换, 区域特征, 医学图像融合, 小波变换

CLC Number: