Volume rendering quantification algorithm for reconstruction of CT volume-rendered structures: Part I. Cerebral arteriovenous malformations.
Volume rendering quantification algorithm for reconstruction of CT volume-rendered structures: Part I. Cerebral arteriovenous malformations.
复制标题
用于重建 CT 体绘制结构的体绘制量化算法：第一部分：脑动静脉畸形。
DOI：
10.1109/42.832956
复制
发表时间：
2000
影响因子：
10.6
通讯作者：
Sweeney,PA
中科院分区：
文献类型：
--
作者：
Jani,AB;Pelizzari,CA;Chen,GT;Roeske,J;Hamilton,RJ;Macdonald,RL;Bova,F;Hoffmann,KR;Sweeney,PA
体绘制是一种可视化技术，在诊断放射学和放射治疗中有重要的应用，但尚未得到广泛使用，部分原因是缺乏体积分析工具来比较体绘制和传统的可视化技术。介绍并描述了体绘制量化算法（VRQA），该算法是一种对六个主要体绘制视图上识别的结构进行三维重建的技术，VRQA主要包括三个步骤：1)对六个体绘制图像中的每个图像构造的局部表面进行预处理；2)合并这些加工过的局部表面来定义一个体的边界；3)根据边界信息计算结构的体积。将VRQA应用于脑动静脉畸形（AVM）患者的CT数据。由于脑动静脉瘤的体积可视化对操作者依赖关系（如不透明传递函数的选择）相对不敏感，并且由于精确的动静脉瘤体积定义对于放射外科治疗计划是必要的，因此它是一类理想的VRQA测试和校准结构的代表。使用VRQA获得的AVM体积介于轴向轮廓和ct相关双平面血管造影术（两种常用的可视化技术用于AVM的治疗计划）之间。讨论了VRQA的应用和潜在的扩展。
Volume rendering is a visualization technique that has important applications in diagnostic radiology and in radiotherapy but has not achieved widespread use due, in part, to the lack of volumetric analysis tools for comparison of volume rendering to conventional visualization techniques. The volume rendering quantification algorithm (VRQA), a technique for three-dimensional (3-D) reconstruction of a structure identified on six principal volume-rendered views, is introduced and described, VRQA involves three major steps: 1) preprocessing of the partial surfaces constructed from each of six volume-rendered images; 2) merging these processed partial surfaces to define the boundaries of a volume; and 3) computation of the volume of the structure from this boundary information. After testing on phantoms, VRQA was applied to CT data of patients with cerebral arteriovenous malformations (AVM's). Because volumetric visualization of the cerebral AVM is relatively insensitive to operator dependencies, such as the choice of opacity transfer function, and because precise volumetric definition of the AVM is necessary for radiosurgical treatment planning, it is representative of a class of structures that is ideal for testing and calibration of VRQA, AVM volumes obtained using VRQA are intermediate to those obtained using axial contouring and those obtained using CT-correlated biplanar angiography (two routinely used visualization techniques for treatment planning for AVM's). Applications and potential expansions of VRQA are discussed.