医学图像可视化的视觉优化方法  

Research on Visual Optimization Method of Medical Image Visualization

作　　者：魏敏 王松[1,2] 吴亚东[1] Wei Min;Wang Song;Wu Yadong(School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010;Institute of Electronic Engineering, China Academy of Engineering Physics, Mianyang 621010)

机构地区：[1]西南科技大学计算机科学与技术学院,绵阳621010 [2]中国工程物理研究院电子工程研究所,绵阳621010

出　　处：《计算机辅助设计与图形学学报》2019年第4期659-667,共9页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家重点研发计划(2016QY04W0801);四川省军民融合研究院开放基金(JMRH01;18xsb030);四川省科技厅科技计划项目(17zs211201;17zs212801);四川省科技创新苗子工程资助项目(2018034)

摘　　要：由于受主观意识和经验等因素的影响,医学图像可视化中传递函数的选择和设置会直接影响医学图像可视化效果.为此,提出一种基于视觉优化的医学图像可视化方法.针对三维医学图像绘制,采用基于GPU加速的光线投射体绘制半自动化传递函数,解决了三维图像全局和焦点上下文的优化显示问题;针对二维图像呈现,借助直方图均衡化、图像融合和全变分模型3种图像增强算法,解决了二维医学图像噪声干扰、对比度模糊和边缘丢失等问题.通过与传统方法的实验对比,三维医学图像在绘制时间和绘制效果方面均有改善;引入图像质量评估指标峰值信噪比和平均结构相似性,验证了全变分模型在二维医学图像增强中的有效性.结合视觉优化方法设计开发了医学图像可视化交互系统,包含对医学数据的三维可视化和交互分析功能,有效地拓展算法的应用性.The transfer function selecting and setting process plays an important role in medical image visualization, and is affected by many factors, such as experience and subjective consciousness. The quality of transfer function is closely related to the performance of medical image visualization. In this paper, a medical image visualization method based on visual optimization is proposed. For the three-dimensional image rendering, the semi-automated transfer function based on the GPU-accelerated ray-cast volume rendering is given, which successfully figures out display problem between the global and the focus context of the three-dimensional image.For the two-dimensional image rendering, three image enhancement algorithms(histogram equalization, image fusion and total variation model) are adopted, which solve the problems, such as two-dimensional image noise,contrast blur and edge loss. Compared with the traditional methods, the proposed three-dimensional medical image visualization method is improved in drawing time and rendering effect. The peak signal to noise ratio and mean structural similarity of the image quality evaluation index are introduced to verify the effectiveness of the total variation model in two-dimensional medical image enhancement. Finally, a visual interactive system for medical images is designed and developed, which includes the three-dimensional visualization and interactive analysis of medical data.

关 键 词：医学图像可视化 传递函数 视觉优化 全变分模型 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]