三维智能PACS相关图形图像技术(英文版)

医学影像分割技术是采 用计算机技术对医学影像 进行辅助处理的基础，是 当前医学图像处理的一个 难点，也是肿瘤量化分析 和精准治疗的基础。鉴于 此，本书提出了三维智能 剪刀算法，把原本仅适用 于二维图像的智能剪刀拓 展到了三维空间，并成功 应用于胸腔分割和肝脏分 割，实现了一套基于三维 智能剪刀的智能PACS（医 学影像存档与传输系统） 。本书分两部分：第一部 分包含4章，主要讨论了基 于仿射变换的三维动画传 输算法，该算法是三维智 能PACS的基础；第二部分 包含2章，讨论了针对医学 影像的三维智能剪刀算法 ，并介绍了该PACS系统的 设计、功能和具体操作界 面。 本书适合图形图像技术 和医学影像处理专业的高 年级本科生、研究生和相 关研究人员。

Part One (Chapters 1~4) Chapter 1 Animating by example 1.1 The significance of the animating-by-example method 1.2 Survevs of related existine research and overview of our method 1.2.1 Surveys of related existing research 1.2.2 Overview of our method 1.3 The main steps of the core algorithm 1.3.1 Sketch based mapping 1.3.2 Differential mean value coordinates for mesh deformation 1.3.3 Stitching and smoothing meshes 1.3.4 Interpolating between key frames 1.3.5 Mapping 2D animations to 3D characters 1.3.6 Solving the minimization problem for smoothing mesh 1.4 Results of the method 1.5 Conclusions of this chapter Chapter 2 A new method of interactive marker-driven free-form mesh deformation 2.1 The related works of free form mesh deformation 2.2 Overview of the new method of free-form mesh deformation 2.3 The main steps of interactive marker-driven free-form mesh deformation 2.3.1 The algorithm of shape deformation 2.3.2 The algorithm of mesh smoothing 2.3.3 Interpolating between two key frames 2.4 Conclusions of this chapter Chapter 3 As-rigid-as-possible deformation clone 3.1 The related works of deformation clone 3.2 Overview of the method 3.3 The algorithm of deformation clone 3.4 The and conclusions of the method 3.4.1 The results of the method proposed in this chapter 3.4.2 The conclusions of the method proposed in this Chapter Chapter 4 A fast trapeziums-based method for soft shadow volumes 4.1 Previous works of soft shadow volumes 4.2 Obtaining soft shadows with ray tracing 4.2.1 Finding out all global potential silhouette edges 4.2.2 Getting local potentíial silhouette edges and exact silhouette edges 4.2.3 Projecting, modifying and spliting silhouette edges 4.2.4 Constructing trapeziums to determine the visibility of light source 4.3 Results and conclusions of the algorithm Part Two (Chapters 5 and 6) Chapter 5 Interactive mesh segmentation and contour optimization for liver & tumors 5.1 The related works of liver and tumors segmentation 5.2 Outline of the approach 5.3 Main steps of the approach 5.3.1 Finding chest bones 5.3.2 Constructing chest mesh 5.3.3 Constructing liver mesh 5.3.4 Extended intelligent scissors 5.3.5 Liver segmentation scheme 5.4 Experiments and results 5.5 Discussion and conclusions of this chapter Chapter 6 Design and development of smart PACS based on 3D intelligent scissors 6.1 Design goals 6.2 Feasibility analvsis 6.3 Main development content 6.3.1 Optimization of 3D intelligent scissors algorithm 6.3.2 Development of smart PACS system 6.3.3 System architecture 6.4 System development and implementation 6.4.1 System modules 6.4.2 Interface and tips of smart PACS 6.5 Video of academic results created by smart PACS Appendix 1: Sparse matrix algorithms and software Appendix 2: Solving the minimization problem Appendix 3: Detailed evaluation results of 40 cases Appendix 4: Detailed evaluation results of 10 cases downloaded from MICCAI database Appendix 5: Introduction to DICOM Appendix 6: Project file format of smart PACS References Index