摘要
目的:为了帮助医生对病变区域进行准确的分析和定位,在显示感兴趣区域的同时,更多地保留上下文信息。方法:保留上下文结构光照模型利用光照信息和数据本身的梯度信息来构建不透明度衰减函数,将该衰减函数与当前采样点的不透明度值相乘,得到该采样点的不透明度,然后进行光线合成。该模型可以在保留上下文结构的基础上达到虚拟剖切的效果,进而有选择地对感兴趣区域进行显示。本文在原有保留上下文体绘制的基础上,对其传递函数进行了改进。通过引入曲率信息,增强边界轮廓,并去除光照因子,保留深度信息,从而设计出一种基于曲率的传递函数模型。结果:该模型在体绘制过程中,增大了位于轮廓线上采样点的不透明度,减弱了光照因子对透明度的衰减,实现了虚拟剖切的效果,并更多地保留了轮廓线,更好的实现了保留上下文结构的绘制效果。结论:本文所提出的新模型通过引入曲率信息后,可以保留组织内部更加丰富的信息,提高了成像效果,可以对医学数据的内部结构进行准确分析,保留感兴趣区域的上下文信息,为医生定位病变区域提供帮助。
Objective： In order to help doctors to locate and analyze the lesion areas, the region of interest need to be displayed while the context cues are well preserved. Methods： Context-preserving volume rendering （CPVR） sets up the opacity attenua- tion function through the information of lighting and gradient. The renewed opacity of the sampling point can be get from the product of the opacity value and attenuated value, which is followed by light Compositing. Based on the original CPVR model, a new model which utilizes the curvature and removes illumination effect is proposed. Results： The experimental results show that the new model can increase the opacity of the sampling points which lie in the contour and weaken the effect of light. Therefore, it can enhance the contours of tissues effectively and simultaneously preserve context cues for the viewer. Conclusions： By the introduction of curvature information, the proposed model can accurately analyze internal structure of the datasets and retain the context information of the region of interest, which will help the physician to locate the lesion areas,
出处
《中国医学物理学杂志》
CSCD
2013年第4期4289-4293,共5页
Chinese Journal of Medical Physics
基金
广东省科技计划项目"2011B090400418"
关键词
体绘制
保留上下文
传递函数
曲率
轮廓
volume rendering
context-preserving
transfer function
curvature contour
