期刊文献+

多模医学图像配准和融合方法及其临床应用进展 被引量:15

Research advances in multi-modality medical image registration and fusion methods and their clinical application
原文传递
导出
摘要 多模医学图像处理是当前图像处理中的研究热点,对于临床诊断和治疗都有着重要的意义。不同模态的图像提供了患者的不同信息,解剖图像(如CT、MRI)提供了人体解剖形态结构的信息,功能图像(如SPECT、PET)提供了人体内放射性浓度分布的功能信息,这些不同信息需要通过合成得到信息更为全面的融合图像。而要得到有用的融合图像,不同模态的图像需经配准处理。这里综述了几种应用于医学领域的图像配准和融合技术,指出了不同技术的各自优缺点,同时也对近期各种处理技术在临床应用中的研究做了介绍。 Multi-modality medical image processing has become a hot topic for research in the field of image processing and plays an important role in clinical diagnosis and treatment. Images with different modalities provide different information on patients. Anatomical images ( such as computed tomography and magnetic resonance imaging ) provide information on anatomical morphology and the structure of human body, and functional images ( such as single-photon emission computed tomography and positron emission tomography) provide the functional information on the distribution of radioactive concentration within human body. Such information needs to be fused to obtain comprehensive fusion images, and the images with different modalities need to be registered to obtain useful fusion images. This article reviews several image registration and fusion techniques used in the medical field, points out their advantages and shortcomings, and introduces the application of various processing techniques in clinical practice.
出处 《中华放射肿瘤学杂志》 CSCD 北大核心 2016年第8期902-906,共5页 Chinese Journal of Radiation Oncology
关键词 图像处理 图像配准 图像融合 Image processing Image registration Image fusion
  • 相关文献

参考文献2

二级参考文献28

  • 1李卫华,周军,周连文,程英蕾.一种基于提升小波分解图像融合方法[J].计算机应用,2006,26(2):403-405. 被引量:9
  • 2苗启广,王宝树.一种自适应PCNN多聚焦图像融合新方法[J].电子与信息学报,2006,28(3):466-470. 被引量:36
  • 3Wilhelm K,Wilsmann-Theis D,Sommer T,et al.CTangiography hemodynamically relevant to renal arterystenosis,evaluation of AXIAL,MPR,MIP and SSDreconstruction procedures under standard investigationconditions[J].ROFO:Fortschritte auf dem Gebiete derRontgenstrahlen und der Nuklearmedizin,2000,172(2):161 167
  • 4Eckhorn R,Reitboeck H J,Arndt M,et al.A neuralnetwork for feature linking via synchronous activity:resultsfrom cat visual cortex and from simulations[C]??Proceedingsof Models of Brain Function.Cambridge:CambridgeUniversity Press,1989:255 272
  • 5Huang W,Jing Z L.Multi-focus image fusion using pulsecoupled neural network[J].Patter Recognition Letters,2007,28(9):1123 1132
  • 6Xu B C,Chen Z.A multisensor image fusion algorithm basedon PCNN[C]??Proceedings of the 5th World Congress onIntelligent Control and Automation.Hangzhou:Institute ofElectrical and Electronics Engineers Inc,2004:3679 3682
  • 7Daubechies I,Sweldens W.Factoring wavelet transforms intolifting steps[J].Journal of Fourier Analysis andApplications,1998,4(3):247 269
  • 8Chavez P S,Sides S C,Anderson J A.Comparison of threedifferent methods to merge multiresolution and multispectraldata:landsat TM and SPOT panchromatic[J].Photogrammetric Engineering&Remote Sensing,1991,57(3):295 303
  • 9Hill P R,Bull D R,Canagarajah C N.Image fusion using anew framework for complex wavelet transforms[C]??Proceedings of IEEE Interational Conference on ImageProcessing.Los Alamitos:IEEE Computer Society Press,2005,2:1338 1341
  • 10GEMMA P. A general framework for multiresolution image fusion: from pixels to regions [ J ]. Information Fusion, 2003,4 ( 4 ) : 295- 280.

共引文献39

同被引文献96

引证文献15

二级引证文献56

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部