医学图象三维重建及可视化技术研究
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摘要
医学图象三维重建是目前的一个研究热点问题，是一个多学科交叉的研究
领域，是计算机图形学和图象处理在生物医学工程中的重要应用。它涉及数字
图象处理、计算机图形学以及医学领域的相关知识。医学图象三维重建及可视
化在诊断医学、手术规划及模拟仿真、整形及假肢外科、放射治疗规划、解剖
教学等方面都有重要应用。同时，此重建方法可用于基于工业CT（ICT）图象的
反求工程中，建立CAD信息模型。因此，对医学图象三维重建的研究，具有
重要的学术意义和应用价值。
医学图象三维表面重建的主要研究内容包括医学图象的预处理，如插值、
滤波等；组织或器官的分割与提取；复杂表面多相组织成份三维几何模型的构
建；重建模型的表面网格简化；模型的剖切与手术开窗操作等。本文对医学图
象（CT、MRI）三维重建的关键技术进行了研究，并开发了一个供放射治疗系统
应用的三维图形图象应用系统。
对组织或器官的分割与提取是保证重建模型准确表达其相应组织器官的
前提。本文提出的分割方法的步骤是先分析各断层图象的灰度直方图和三维图
象的整体灰度直方图，交互给定分割阈值的上限和下限，对三维图象二值化；
然后根据待重建组织的形态特征选取合适的形态学操作进行区域修整；最后用
种子填充算法来填充出要分割的区域。
Marching Cubes（MC）算法是基于规则体数据抽取等值面的经典算法，
Marching Tetrahedra（MT）算法是MC算法的改进和变型。本文实现了这两种算
法对分割提取的区域抽取等值面构建表面模型，并针对MT算法存在重建速度
慢、数据存储冗余等缺点，提出了体素内相关性处理和体素间相关性处理方法。
采用本文的相关性处理，可加快重建速度。
采用MC和MT算法抽取等值面构建的表面几何模型所包含的三角面片数
量巨大，难以实现实时绘制显示。本文以Hoppe等人提出的边收缩算法为基
础，设计了表面模型的网格简化算法，并实现了重建模型的网格简化。运行实
例表明，模型的网格简化90％后，依然能保持原模型的特征和较好的视觉效
果。重建模型经网格简化，可大大提高实时交互绘制能力。
为便于观察组织各截面的大小和形状、内部组织的结构和空间位置，本文
提出了一种对重建组织实施剖切和选定视窗剪裁的方法。该方法用剖切面或剖
切体对重建模型施以剖切，在剖切面上生成边序列及顶点序列；由此边序列和
顶点序列生成封闭的边界轮廓，确定各轮廓的包含关系；对封闭轮廓包围的截
面区域进行 Delaunay三角剖分，得到完整的剖切后的表面模型。模型被剖切
或开窗，可以方便看到内部的组织，便于观察和诊断。
论文还探讨了由表面模型转化成B1ep表示的实体几何模型的方法。简要
介绍了由对应轮廓重建表面模型的方法及步骤，分析了实体几何模型的数据结
构及造型的基本操作，提出了基于轮廓重建的表面模型构建实体几何模型的方
法和实现步骤。由仅具有表面几何信息的表面模型转化为具有完备的几何和拓
扑信息的实体模型。由表面模型构建实体模型在反求工程中有着重要应用，如
由工业CT（ICT）获取的二维序列图象经轮廓提取、表面拟合后转化成B－rep表
示的实体几何模型，该实体模型的数据格式可为通用CAI）造型系统所接受，可
作为反求工程的一种造型方式。
论文最后综述了适用于适形调强放射治疗的医学图象三维重建系统的开
发。分析了重建系统的程序流程，对系统进行了模块划分，提出并建立了系统
数据结构。数据结构清晰描述系统数据的层次关系，正确表达重建几何模型的
几何信息，合理表达模型与模型、模型内部几何元素之间的关系，实现对重建
模型的记录、管理与操作。提出了自动分割与手工勾画轮廓的方法。对分割出
的组织重建其三维几何模型，并对模型实现了网格简化。实现了治疗射束的设
置及多叶光栅轮廓的计算。
3D reconstruction from medical images is a multi-disciplinary subject. It is an important application of computer graphics and image processing in biomedicine engineering. It relates to the subjects of digital image processing, computer graphics and some related knowledge of medical. 3D reconstruction and visualization of medical images are widely used in diagnostic, surgery planning and simulating, plastic and artificial limb surgery, radiotherapy planning, and teaching in anatomy. Also, the reconstruction method can be used in reverse engineering to build CAD models, such as to build solid models based on industry computed tomography (ICT) images. Study on 3D reconstruction from medical images has important significance on science and worthiness in practical application.
The main research contents of 3D surface reconstruction from medical images include image pre-processing, such as interpolating and filtering, segmenting and extracting tissues or organs of body, constructing 3D surface models, simplifying of meshes of the models, and cutting or stereo clipping the model. In this dissertation, key techniques for 3D reconstructing from medical images (such as CT, MRI images) are studied, and a 3D reconstruction system used for radiotherapy is developed.
Segmenting and extracting tissues or organs from medical images are premises of 3D reconstruction models accurately. In this dissertation, an interactive segmentation method of 3D medical images based on gray-level information is presented. The segmentation process consists of following steps: filtering the images, creating the threshold values after analyzing the gray-level histograms of the whole 3D image and some slice images, binarizing the images, processing the images using properly mathematical morphology operation according to the feature of tissues or regions to extract, and filling the regions using seed fill algorithm.
Marching cubes (MC) algorithm is a classical algorithm to extract iso-surface from regular volume data. Marching tetrahedra (MT) algorithm is improved based on MC algorithm. This dissertation has implemented these two algorithm to extract iso-surface from the segmented regions. 3D surface models are built up. MT algorithm has disadvantages of low reconstructing speed and data redundancy. To improve this algorithm performance, methods to deal with the relativities among tetrahedra in one voxel and relativities among voxels are developed. With the methods, repeated interpolating calculation is avoided, and surface reconstructing is speed up.
3D surface model reconstructed with MC or MT algorithm contains huge number of triangles. It is quite difficult to render them in real time. A modified
i
mesh simplification algorithm based on edges collapse algorithm presented by Hoppe has been designed. Surface models are simplified by using the algorithm. Running examples show that even 90 percent triangles had been reduced, the model still maintains the feature of the original.
In order to analyze section of the reconstructed tissues and observe the size and structure of inner tissues in multi-tissue reconstruction and visualization, methods of cutting and stereo clipping of the reconstructed 3D models are presented. The 3D models are cut by a plane or a polyhedron. Lists of edges and vertexes in every cut plane are established. From these lists, the boundary contours are created and their relationship of embrace is ascertained. The region enclosed by the contours is triangulated using Delaunay triangulation algorithm. The visual model still maintains its correct topology structure. With these operations, inner tissues can be observed easily and it can aid doctors to diagnose.
A method for building boundary representation solid model from surface model is presented in the dissertation. The steps of building surface geometry model from contours, data structure of solid geometry model and fundamental operations of modeling are discussed. Solid model including full geometry and topology information is built from surface model. This ap
领域，是计算机图形学和图象处理在生物医学工程中的重要应用。它涉及数字
图象处理、计算机图形学以及医学领域的相关知识。医学图象三维重建及可视
化在诊断医学、手术规划及模拟仿真、整形及假肢外科、放射治疗规划、解剖
教学等方面都有重要应用。同时，此重建方法可用于基于工业CT（ICT）图象的
反求工程中，建立CAD信息模型。因此，对医学图象三维重建的研究，具有
重要的学术意义和应用价值。
医学图象三维表面重建的主要研究内容包括医学图象的预处理，如插值、
滤波等；组织或器官的分割与提取；复杂表面多相组织成份三维几何模型的构
建；重建模型的表面网格简化；模型的剖切与手术开窗操作等。本文对医学图
象（CT、MRI）三维重建的关键技术进行了研究，并开发了一个供放射治疗系统
应用的三维图形图象应用系统。
对组织或器官的分割与提取是保证重建模型准确表达其相应组织器官的
前提。本文提出的分割方法的步骤是先分析各断层图象的灰度直方图和三维图
象的整体灰度直方图，交互给定分割阈值的上限和下限，对三维图象二值化；
然后根据待重建组织的形态特征选取合适的形态学操作进行区域修整；最后用
种子填充算法来填充出要分割的区域。
Marching Cubes（MC）算法是基于规则体数据抽取等值面的经典算法，
Marching Tetrahedra（MT）算法是MC算法的改进和变型。本文实现了这两种算
法对分割提取的区域抽取等值面构建表面模型，并针对MT算法存在重建速度
慢、数据存储冗余等缺点，提出了体素内相关性处理和体素间相关性处理方法。
采用本文的相关性处理，可加快重建速度。
采用MC和MT算法抽取等值面构建的表面几何模型所包含的三角面片数
量巨大，难以实现实时绘制显示。本文以Hoppe等人提出的边收缩算法为基
础，设计了表面模型的网格简化算法，并实现了重建模型的网格简化。运行实
例表明，模型的网格简化90％后，依然能保持原模型的特征和较好的视觉效
果。重建模型经网格简化，可大大提高实时交互绘制能力。
为便于观察组织各截面的大小和形状、内部组织的结构和空间位置，本文
提出了一种对重建组织实施剖切和选定视窗剪裁的方法。该方法用剖切面或剖
切体对重建模型施以剖切，在剖切面上生成边序列及顶点序列；由此边序列和
顶点序列生成封闭的边界轮廓，确定各轮廓的包含关系；对封闭轮廓包围的截
面区域进行 Delaunay三角剖分，得到完整的剖切后的表面模型。模型被剖切
或开窗，可以方便看到内部的组织，便于观察和诊断。
论文还探讨了由表面模型转化成B1ep表示的实体几何模型的方法。简要
介绍了由对应轮廓重建表面模型的方法及步骤，分析了实体几何模型的数据结
构及造型的基本操作，提出了基于轮廓重建的表面模型构建实体几何模型的方
法和实现步骤。由仅具有表面几何信息的表面模型转化为具有完备的几何和拓
扑信息的实体模型。由表面模型构建实体模型在反求工程中有着重要应用，如
由工业CT（ICT）获取的二维序列图象经轮廓提取、表面拟合后转化成B－rep表
示的实体几何模型，该实体模型的数据格式可为通用CAI）造型系统所接受，可
作为反求工程的一种造型方式。
论文最后综述了适用于适形调强放射治疗的医学图象三维重建系统的开
发。分析了重建系统的程序流程，对系统进行了模块划分，提出并建立了系统
数据结构。数据结构清晰描述系统数据的层次关系，正确表达重建几何模型的
几何信息，合理表达模型与模型、模型内部几何元素之间的关系，实现对重建
模型的记录、管理与操作。提出了自动分割与手工勾画轮廓的方法。对分割出
的组织重建其三维几何模型，并对模型实现了网格简化。实现了治疗射束的设
置及多叶光栅轮廓的计算。
3D reconstruction from medical images is a multi-disciplinary subject. It is an important application of computer graphics and image processing in biomedicine engineering. It relates to the subjects of digital image processing, computer graphics and some related knowledge of medical. 3D reconstruction and visualization of medical images are widely used in diagnostic, surgery planning and simulating, plastic and artificial limb surgery, radiotherapy planning, and teaching in anatomy. Also, the reconstruction method can be used in reverse engineering to build CAD models, such as to build solid models based on industry computed tomography (ICT) images. Study on 3D reconstruction from medical images has important significance on science and worthiness in practical application.
The main research contents of 3D surface reconstruction from medical images include image pre-processing, such as interpolating and filtering, segmenting and extracting tissues or organs of body, constructing 3D surface models, simplifying of meshes of the models, and cutting or stereo clipping the model. In this dissertation, key techniques for 3D reconstructing from medical images (such as CT, MRI images) are studied, and a 3D reconstruction system used for radiotherapy is developed.
Segmenting and extracting tissues or organs from medical images are premises of 3D reconstruction models accurately. In this dissertation, an interactive segmentation method of 3D medical images based on gray-level information is presented. The segmentation process consists of following steps: filtering the images, creating the threshold values after analyzing the gray-level histograms of the whole 3D image and some slice images, binarizing the images, processing the images using properly mathematical morphology operation according to the feature of tissues or regions to extract, and filling the regions using seed fill algorithm.
Marching cubes (MC) algorithm is a classical algorithm to extract iso-surface from regular volume data. Marching tetrahedra (MT) algorithm is improved based on MC algorithm. This dissertation has implemented these two algorithm to extract iso-surface from the segmented regions. 3D surface models are built up. MT algorithm has disadvantages of low reconstructing speed and data redundancy. To improve this algorithm performance, methods to deal with the relativities among tetrahedra in one voxel and relativities among voxels are developed. With the methods, repeated interpolating calculation is avoided, and surface reconstructing is speed up.
3D surface model reconstructed with MC or MT algorithm contains huge number of triangles. It is quite difficult to render them in real time. A modified
i
mesh simplification algorithm based on edges collapse algorithm presented by Hoppe has been designed. Surface models are simplified by using the algorithm. Running examples show that even 90 percent triangles had been reduced, the model still maintains the feature of the original.
In order to analyze section of the reconstructed tissues and observe the size and structure of inner tissues in multi-tissue reconstruction and visualization, methods of cutting and stereo clipping of the reconstructed 3D models are presented. The 3D models are cut by a plane or a polyhedron. Lists of edges and vertexes in every cut plane are established. From these lists, the boundary contours are created and their relationship of embrace is ascertained. The region enclosed by the contours is triangulated using Delaunay triangulation algorithm. The visual model still maintains its correct topology structure. With these operations, inner tissues can be observed easily and it can aid doctors to diagnose.
A method for building boundary representation solid model from surface model is presented in the dissertation. The steps of building surface geometry model from contours, data structure of solid geometry model and fundamental operations of modeling are discussed. Solid model including full geometry and topology information is built from surface model. This ap
引文
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