多模医学图像配准和融合方法及其临床应用进展

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。

Research advances in multi-modality medical image registration and fusion methods and their clinical application

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.