一种基于语义模型的医学图像配准方法  

Medical Image Registration Method Based on a Semantic Model with Directional Visual Words

作　　者：金雨菲[1] 麻蒙 杨新[1] 

机构地区：[1]上海交通大学图像处理与模式识别所,上海200240

出　　处：《生物医学工程学杂志》2016年第2期343-349,共7页Journal of Biomedical Engineering

基　　金：国家"973"资助项目(2010CB732506);上海市科委重点资助项目(12JC1406600)

摘　　要：医学图像由于成像模式、图像质量、患者间及患者在不同病程时的图像变化等差异以及对鲁棒性的严格要求,它的配准成为难点。我们受语义模型,尤其是视觉词包模型在计算机视觉中巨大成功的启发,将语义模型推广到医学图像配准。由于医学图像大都具有对比度差、动态范围小、只含灰度信息等特点,传统的视觉词包往往效果不够理想。本文根据相关研究工作,提出了更适用于医学图像处理的方向性视觉词包模型,并基于该语义模型进行医学图像配准。我们由专家人工指定关键的解剖结构,使用方向性视觉词包,借助由粗到细的金字塔搜索策略和k-means聚类方法,准确定位关键结构的位置,并重点配准它们附近的区域。在心脏图像上进行的实验表明,该方法可保证在特定区域内达到较高的配准精度。Medical image registration is very challenging due to the various imaging modality,image quality,wide inter-patients variability,and intra-patient variability with disease progressing of medical images,with strict requirement for robustness.Inspired by semantic model,especially the recent tremendous progress in computer vision tasks under bag-of-visual-word framework,we set up a novel semantic model to match medical images.Since most of medical images have poor contrast,small dynamic range,and involving only intensities and so on,the traditional visual word models do not perform very well.To benefit from the advantages from the relative works,we proposed a novel visual word model named directional visual words,which performs better on medical images.Then we applied this model to do medical registration.In our experiment,the critical anatomical structures were first manually specified by experts.Then we adopted the directional visual word,the strategy of spatial pyramid searching from coarse to fine,and the k-means algorithm to help us locating the positions of the key structures accurately.Sequentially,we shall register corresponding images by the areas around these positions.The results of the experiments which were performed on real cardiac images showed that our method could achieve high registration accuracy in some specific areas.

关 键 词：医学图像配准 语义模型 方向性视觉词包 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]