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