基于工业CT断层图像的三维可视化

工业CT图像三维可视化能够对工业构件提供真实、直观的反映。体绘制技术可以显示工业CT三维数据的整体特征和内部细节信息。根据光线投射算法的特点，采用对原始数据场进行最大熵原则的预处理的方法，加快了绘制速度，在一定程度上改进了光线投射算法，取得了较好的显示效果。     

基于多等值面的工业CT三维显示与测量

结合大型工业CT中对缺陷检测、参数测量、空间密度分布检测等工程应用要求,研究了应用于工业CT缺陷检测的表面绘制可视化检查技术。基于Marching Cube算法构造等值面的原理,分析了分析工业CT检测对象特点和先验知识,设计了工业CT工件模型化区域多等值面可视化检查的方法,在OpenGL面绘制中实现了基于深度缓存的交互式标定测量的原理和算法,为工业CT体数据的三维可视化检查提供有力的手段。     

显微三维分析软件设计与开发

论述了显微三维分析软件系统的组织结构和程序流程; 针对因离焦光线的干扰而产生的模糊光学断层图像序列, 基于断层内相邻像素和断层间相邻像素的相关信息, 采用改进的最大期望算法对光学断层图像序列进行去模糊处理; 对去模糊处理后的三维光学断层图像序列, 介绍了一种基于表面点绘制的三维数据场表面重建反走样方法, 加快了重建速度, 同时具有较好的显示效果; 三维体绘制时, 提出了多维半自动阻光度转换函数解决方案, 清晰地显示出了物体内部的细节变化; 采用基于体素的方法计算重建后的物体的表面积和体积; 通过三维分割和标记算法, 实现了在三维空间内选择感兴趣目标的操作。     

改进的三维可视化用光线投射算法

把图像处理、光线投射与包围体技术有机结合，提出了一种提高成像质量和速度的三维可视化新方法。该方法利用物体空间的包围体算法来减少追踪光线的数量，加快了绘制速度。通过实际的医学胸部CT图像的三维重建实验，取得了较好的三维显示效果和速度，验证了改进的光线投射算法对胸部CT图像的快速三维可视化问题的有效性。     

体层次迭代发射算法

本文介绍体层次迭代发射算法 ,它用于虚拟现实图形演示的体放射法。基于体单元对光线的发射、吸收、漫射、反射和散射基础上的体放射法 ,适用于复杂景物的生成和演示 ,在真实感图形演示中具有重要地位。本文首先介绍体放射法的主要技术细节 ,如光线计算 ,体放射方程 ,光线生成参数 ,接着说明体层次发射算法的机理 ,最后给出了本算法生成的实例。同时对算法还做了评估。     

一种改进的光线投射方法

光线投射算法是体绘制中的经典算法,但其绘制速度较慢。本文对传统的光线投射算法中等间距重采样进行了改进,引入包围盒方法,采用变步长的采样方法,减少冗余数据量和投射光线数量,优化重采样过程,提高采样效率。医学图像可视化实验表明,改进方法能够在保证图像质量的同时,提高绘制速度。     

基于Map Reduce的多序列星比对方法在肿瘤研究中的应用

序列比对是生物信息学的基础,通过多条序列比对可以挖掘出生物序列中的各种重要信息。大规模的基因序列比对方法对运算能力要求较高,基于Map Reduce框架的多序列比对方法在多序列星比对算法的基础上利用分布式并行计算来处理大规模数据。实验结果表明：相对于单机处理方法,基于Map Reduce的序列比对方法可以更快速地处理大规模数据,并且具有良好的硬件扩展性。本文探讨了多序列比对在肿瘤研究方面的应用前景。     

由CT三维数据重建物体曲面剖面技术研究

用X-CT设备对被检测物体扫描后获得了一系列的二维图像,然后通过计算机图形图像学中的可视化技术从这些二维图像中重建出物体内部的三维结构。这正成为无损检测中一项重要的技术。而重建被检测物体的任意剖面的技术正是三维可视化技术的重要组成部分。本文在总结以前绘制物体任意剖面的众多方法基础上,对其中主要两种任意剖面方法进行深入探讨和比较研究,针对绘制曲面剖面的重采样困难,并结合基于体元的剖面直接生成方法的内在特点,在不影响剖面图像质量的前提下,提出了绘制曲面剖面的近似方法,而且使用数据预处理技术对其算法进行改进,大大提高了运算速度,达到实时绘制的要求。这改进的方法不仅能够绘制任意平面剖面,而且能够绘制包括球面等曲面剖面,因而它具有良好的扩展性和广阔的应用前景。     

基于高性能图形并行计算的手机3D游戏解决方案

随着3G技术的发展,手机游戏在人们的生活和娱乐中扮演着越来越重要的角色。目前,受到硬件条件的限制,在手机平台上很难开发出类似于PC机上的大型3D游戏。本文提出了基于Chro-mium的GPU并行绘制技术,使得大部分OpenGL游戏或其它OpenGL应用程序能够在我们开发的系统上直接运行,它能够自动地截获应用程序的3D模型数据及其绘制信息、生成多视点图像;将3D图形计算的任务交给服务器而非手机本身,使得3D画面效果不再受到手机计算能力的制约;利用远程绘制模式,将绘制完成的多视点图像通过网络发送给手机,实现手机上的3D自由立体显示。另一方面,用户利用手机与游戏系统进行交互,从而控制服务器实时地生成具有自由立体显示效果的3D游戏画面,并在手机上实时地显示,使得人们可以通过手机终端,体验到大型3D立体游戏的乐趣。     

工业过程断层图像的三维动态可视化

提出了一种针对工业过程断层图像的三维动态可视化方法,可用于对工业过程的辅助监控。该方法采用基于光线投射的体可视化技术,已在MITK(Medical Imaging ToolKit,一个用于医学影像处理与分析的C++类库)中实现。该方法使用不同的颜色和阻光度系数来区分反应容器或管道中的不同物质,从而为容器或管道中不同物质的混合反应过程提供一个动态的显示。实验结果证明该方法是可行的,并且其性能也是可接受的,若再辅之以体绘制算法的硬件加速,该方法可用于实时的工业断层成像系统中。     

Volumetric visualization of head and neck CT data for treatment planning.

PURPOSE: To demonstrate the utility of volume rendering, an alternative visualization technique to surface rendering, in the practice of CT based radiotherapy planning for the head and neck. METHODS AND MATERIALS: Rendo-avs, a volume visualization tool developed at the University of Chicago, was used to volume render head and neck CT scans from two cases. Rendo-avs is a volume rendering tool operating within the graphical user interface environment of AVS (Application Visualization System). Users adjust the opacity of various tissues by defining the opacity transfer function (OTF), a function which preclassifies voxels by opacity prior to rendering. By defining the opacity map (OTF), the user selectively enhances and suppresses structures of various intensity. Additional graphics tools are available within the AVS network, allowing for the manipulation of perspective, field of view, data orientation. Users may draw directly on volume rendered images, create a partial surface, and thereby correlate objects in the 3D scene to points on original axial slices. Information in volume rendered images is mapped into the original CT slices via a Z buffer, which contains the depth information (Z coordinate) for each pixel in the rendered view. Locally developed software was used to project conventionally designed GTV contours onto volume rendered images. RESULTS: The lymph nodes, salivary glands, vessels, and airway are visualized in detail without prior manual segmentation. Volume rendering can be used to explore the finer anatomic structures that appear on consecutive axial slices as "points." Rendo-avs allowed for acceptable interactivity, with a processing time of approximately 5 seconds per 256 x 256 pixel output image. CONCLUSIONS: Volume rendering is a useful alternative to surface rendering, offering high-quality visualization, 3D anatomic delineation, and time savings to the user, due to the elimination of manual segmentation as a preprocessing step. Volume rendered images can be merged with conventional treatment planning images to add anatomic information to the treatment planning process.     

High-performance GPU-based rendering for real-time, rigid 2D/3D-image registration and motion prediction in radiation oncology

A common problem in image-guided radiation therapy (IGRT) of lung cancer as well as other malignant diseases is the compensation of periodic and aperiodic motion during dose delivery. Modern systems for image-guided radiation oncology allow for the acquisition of cone-beam computed tomography data in the treatment room as well as the acquisition of planar radiographs during the treatment. A mid-term research goal is the compensation of tumor target volume motion by 2D/3D Registration. In 2D/3D registration, spatial information on organ location is derived by an iterative comparison of perspective volume renderings, so-called digitally rendered radiographs (DRR) from computed tomography volume data, and planar reference x-rays. Currently, this rendering process is very time consuming, and real-time registration, which should at least provide data on organ position in less than a second, has not come into existence. We present two GPU-based rendering algorithms which generate a DRR of 512×512 pixels size from a CT dataset of 53 MB size at a pace of almost 100 Hz. This rendering rate is feasible by applying a number of algorithmic simplifications which range from alternative volume-driven rendering approaches - namely so-called wobbled splatting - to sub-sampling of the DRR-image by means of specialized raycasting techniques. Furthermore, general purpose graphics processing unit (GPGPU) programming paradigms were consequently utilized. Rendering quality and performance as well as the influence on the quality and performance of the overall registration process were measured and analyzed in detail. The results show that both methods are competitive and pave the way for fast motion compensation by rigid and possibly even non-rigid 2D/3D registration and, beyond that, adaptive filtering of motion models in IGRT.     

基于色素浓度的黄瓜叶片渲染

提出一种基于多种色素浓度的植物叶片方法,以黄瓜为研究对象,通过对正常生长状态下的黄瓜叶片图像采集及叶内多种色素浓度值测定,建立黄瓜叶片颜色分量与多种色素浓度值的数学关系模型,并采用均方根误差（RMSE）对模型进行验证。结果显示叶片的3个颜色分量R（红）、G（绿）、B（蓝）的实测值与模拟值之间的RMSE为9.12%、8.83%、4.40%,模拟效果较好。通过结合物理光照模型并采用高级着色器语言对叶片表观颜色进行可视化模拟,实现了结合植物叶片生理知识和物理感观的黄瓜叶片渲染,并获得了较好的真实感效果。     

Principal component analysis-based pattern analysis of dose-volume histograms and influence on rectal toxicity

PURPOSE: The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. METHODS AND MATERIALS: PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as "eigenmodes," which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. RESULTS: Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe approximately 94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses ( approximately 40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. CONCLUSIONS: PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches.     

Use of principal component analysis to evaluate the partial organ tolerance of normal tissues to radiation

PURPOSE: To describe a novel method of analyzing partial volume effects of normal tissues to radiation. With this approach, principal component analysis (PCA) is used to efficiently describe the variance in cumulative dose-volume histogram (cDVH) morphology. The independent features of cDVHs that describe the largest variance are then investigated regarding complication risk. METHODS AND MATERIALS: Principal component analysis was used to describe the variance in the morphology of normal tissue cDVHs, irrespective of complication, by summarizing the largest source of variation within the first principal component (PC), the next largest in the second PC, and so on. Plots relating the most meaningful PCs were constructed. Ideally, cDVHs associated with a complication would yield PC values that could be easily segregated from cDVHs without a complication. Two data sets were evaluated with this approach: 90 parotid gland cDVHs (36 with complications) and 203 liver cDVHs (19 with complications). RESULTS: Ninety-four percent and 80% of the variation in cDVH morphology was described with two PCs for the parotid gland and the liver data sets, respectively. Plots of the first and second PC values on a Cartesian plane for both data sets revealed "clusters." For the parotid gland, one cluster contained PCs from parotid gland cDVHs with complications, and the other primarily contained PCs from cDVHs without complications. The first PC value, corresponding to a larger volume treated with 10-60 Gy (2 Gy per fraction), was more likely to be larger in parotid gland cDVHs associated with complications than those without complications. In the plots of PC values of liver cDVHs, whole liver radiation cDVHs were segregated from the other cDVHs. There was a trend for cDVHs with a higher first PC, corresponding to increased volume treated with approximately 10-40 Gy (1.5 Gy b.i.d.), to be associated with increased risk of complication. For partial liver radiation cDVHs there was a trend for cDVHs with a higher first PC, corresponding to an increased volume treated with 5-50 Gy, to be associated with a complication. For each data set, logistic regression modeling revealed that the first PC was significantly associated with a complication developing (p < 0.02). CONCLUSIONS: Principal component analysis can be used to summarize the variance in parallel normal tissue cDVHs, and it can help segregate cDVHs at high or low risk for complications.     

Contouring structures for 3-dimensional treatment planning.

Three-dimensional (3-D) treatment planning is a labor-intensive process with contouring of the target volume and critical normal tissues being a significant time-consuming component. The use of 3-D treatment planning on a routine basis may be limited by the time required to complete treatment plans. Despite the need to increase the efficiency of the process, there is little literature addressing the speed and accuracy of contouring systems. In an attempt to initiate systematic analysis of the contouring process, data sets consisting of 10 CT images each were developed on two patients with esophageal carcinoma. Nine different operators manually contoured structures (target volume, spinal canal, lungs) on the data sets using four different contouring systems present in our department. These included both commercially available systems and those developed by the authors. There was a wide variation in the hardware and software characteristics of these systems. The time required to contour the CT data sets was recorded and analyzed. The contouring accuracy was assessed by comparison with a standard template derived from the CT data set for each image. The contouring time was found to be dependent on the system design, previous contouring experience, and the type of drawing instrument (lightpen vs mouse). The mean contouring time ranged from 26 minutes per patient for the fastest system to 41 minutes for the slowest. Potential clinically significant errors in contouring were rare for the spinal canal and lungs but present at a greater rate for the target volume (30.3%). The implications of this finding are discussed.     

A three-dimensional volume visualization package applied to stereotactic radiosurgery treatment planning

A comprehensive software package has been developed for visualization and analysis of 3-dimensional data sets. The system offers a variety of 2- and 3-dimensional display facilities including highly realistic volume rendered images generated directly from the data set. The package has been specifically modified and successfully used for stereotactic radiosurgery treatment planning. The stereotactic coordinate transformation is determined by finding the localization frame automatically in the CT volume. Treatment arcs are specified interactively and displayed as paths on 3-dimensional anatomical surfaces. The resulting dose distribution is displayed using traditional 2-dimensional displays or as an isodose surface composited with underlying anatomy and the target volume. Dose volume histogram analysis is an integral part of the system. This paper gives an overview of volume rendering methods and describes the application of these tools to stereotactic radiosurgery treatment planning.     

The Introduction of Personal Computers into Clinical Cancer Research in Norway

Present and estimated future use of personal computers (PCs) in clinical cancer research was assessed after the distribution of 24 personal computers to clinicians and scientists engaged in clinical cancer research. Two questionnaires were sent to the clinicians with an interval of six months. the clinicians were divided into two main groups, 'Experts' and 'Non-experts', based on their background knowledge of and previous experience with computers. Word processing and recording of patient details were the main application fields for the PC. Requested tasks for future were the performance of statistical analyses and graphics. the clinicians, especially the Non-experts, met the following problems upon the reception of the PC: Lack of time and help to become acquainted with the PC, as well as lack of appropriate software. Half of the clinicians were reluctant to admit any usefulness of artificial intelligence for clinical cancer care. It is concluded that the introduction of personal computers will probably improve the facilities for clinical cancer research. However. clinicians need sufficient time and help to get started, and appropriate software must also be provided.