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适用于三维微血管成像的定量分析方法

Quantitative analysis for 3D micro-vessel imaging

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【作者】 周密谷圣美赵俊

【Author】 ZHOU Mi~1,GU Shengmei~(2,3),ZHAO Jun~1 1 School of Biomedical Engineering,Shanghai Jiao Tong University,Shanghai 200030 2 Department of Breast Surgery,Fudan University Shanghai Cancer Center,Shanghai 200032 3 Department of Oncology,Shanghai Medical College of Fudan University,Shanghai 200032

【机构】 上海交通大学生物医学工稃学院复旦大学附属肿瘤医院乳腺外科复旦大学上海医学院肿瘤学系上海交通大学生物医学工程学院

【摘要】 目的随着高分辨率三维成像技术的发展,微血管成像已成为临床诊断和实验研究的重要手段。为了在定性观察的基础上定量分析血管形态,本文提出一套完整的图像处理方法,并基于此设计了包括血管分割、血管细化、定量分析在内的血管形态分析流程。方法首先利用数学形态学方法实现血管结构提取,接着给出计算血管密度、直径等指标的方法,并引入血管的"卷曲度"参数,以衡量血管的扭曲或异常程度。结果将上述方法应用于1个肝脏血管和3个肿瘤血管灌注成像实例,统计各项形态指标,发现肝脏血管和肿瘤血管在血管密度、分支结构、直径分布以及卷曲度方面均有较大不同。结论本文方法可有效定量三维血管结构,不仅能够定量较为规则的肝脏血管的形态特征,而且对于尺寸更小、结构更精细的肿瘤血管也能准确地定量分析,因此可以为肿瘤的早期诊断和药物治疗的效果追踪提供重要依据。

【Abstract】 Objective With the development of high-resolution computed tomography,micro-vessel imaging has become an important tool for clinical diagnosis and fundamental research.A novel image analysis procedure based on micro-vessel imaging including vessel segmentation,vessel thinning and quantification,is proposed to analyze the vessel morphology qualitatively and quantitatively.Methods The vessel structures are extracted by using mathematical morphology,and then the methods of measuring vessel density and branch diameter are given.Apart from that,the mathematical expression of "tortuosity" is defined to quantitatively analyze tortuous abnormal vessels.Results The algorithm is tested on four experiment data sets including one liver angiographic image and three tumor angiographic images.There are distinctive differences between liver vessels and tumor vessels in vessel density,tree pattern,diameter and tortuosity.Conclusions The paper introduces an effective way of analyzing vessel morphology.The algorithm works well in both normal and abnormal vessels of different sizes,which proves great potential for future application in detecting the development of tumors as well as tracking the treatment effect.

【基金】 973计划(2010CB834302)资助
  • 【文献出处】 北京生物医学工程 ,Beijing Biomedical Engineering , 编辑部邮箱 ,2013年02期
  • 【分类号】R310
  • 【被引频次】10
  • 【下载频次】91
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