VOLUME RENDERING AND MANIPULATION IN TOMOGRAPGIC IMAGING

测量的数据，如由断层扫描设备生成的图像， 本质上不精确。以前和目前的大多数方法都是为了 结构的可视化和分析依赖于对 以这样或那样的方式精确地基于普通(硬)集合的结构 理论。所谓的体绘制过程认识到有必要 以某种方式对不精确本身进行建模。虽然背后的哲学 体绘制看起来非常自然，它并没有被追求超越3D 结构可视化。此外，即使限制在可视化范围内， 高昂的计算和存储成本使其很难 使用体绘制来开发许多重要的应用程序。多数 重要的是，还不可能在 可量化的方式，例如测量和处理它们，一个 这一能力正越来越多地用于各种诊断 治疗和生物医学研究应用。 本研究的具体目的是进行交互式渲染， 测量和操纵结构，所有这些都在体绘制中 范例，可行。该方法包括概括现象，如 作为渲染、隐藏部件移除、操作和测量， 从普通集到模糊集。在这个过程中，效率 保留了基于普通集合的算法。这一概念 通过概念赋予体绘制现象一种结构 指(模糊连接的)模糊对象和模糊边界。 这项研究的一个长期目标是开发用于 多维结构的分析(例如，心脏运动和关节 运动学)使用模糊理论从测量的图像序列中 子集。这似乎是一个非常明智和有用的方向。

Measured data, such as the images generated by tomographic devices, are inherently imprecise . Previous, and a majority of current approaches, to visualization and analysis of structures have relied on modeling the structures precisely based, in one way or another, on ordinary (hard) set theory. The so called volume rendering processes recognized the need to somehow model the imprecision itself. While the philosophy underlying volume rendering seems very natural, it has not been pursued beyond just 3D structure visualization. Additionally, confining even to visualization, the intense computational and storage costs have made it difficult to pursue many important applications using volume rendering. Most importantly, it has not been possible to analyze structures in a quantifiable fashion, for example to measure and manipulate them, an ability which is increasingly being used in a variety of diagnostic therapeutic, and biomedical research applications. The specific aims of this research are to make interactive rendering, measurement, and manipulation of structures, all in the volume rendering paradigm, feasible. The approach consists of generalizing phenomena such as rendering, hidden-part removal, manipulation, and measurement that are based on ordinary sets to fuzzy sets. In the process, the efficiency of the algorithms that are based on ordinary sets are retained. The notion of a structure is imparted to volume rendering phenomenon through the notion of (fuzzily connected) fuzzy objects and fuzzy boundaries. A long-term goal of this research is to develop theory and algorithms for the analysis of multidimensional structures (e.g., cardiac motion and joint kinematics) from measured image sequences using the theory of fuzzy subsets. This seems to be a very sensible and useful direction to pursue.