基于医用X-CT的三维重建系统研究

根据CT图像特点,运用计算机图形、图像和三维可视化技术,开发了一套基于医用X-CT的三维重建原型系统,实现对二维有序CT的浏览、图像分割及重建图像显示等操作.介绍了系统的结构和各种算法的实现.试验结果表明,该系统满足临床辅助诊断和手术计划制定的要求.     

基于等值面构造的CT图像三维重构

现代医学图像与计算机技术的发展以及它们之间的相互融合,使得基于CT的快速成型制造和三维可视化医学辅助系统的设计与开发成为现实.针对医学CT图像三维重建的关键技术,分析并利用等值面构造法进行CT图像的三维构造.分析了标准MC算法计算量大且不易实现的不足,并把SMC(special MC)算法应用到医用螺旋CT图像上进行三维重建.对两种算法进行了实例验证与比较.     

基于Co-60放射源的锥束CT成像系统的研究

图像引导系统由于能帮助对肿瘤靶区进行精确定位,在直线加速器放疗设备上得到了成功应用.考虑到γ射线立体定向放疗设备的机械结构的特殊性,本文拟开发基于Co-60的图像引导装置.为此本文设计并安装了以Co-60为放射源的锥束CT成像系统.在该系统上成功地实现了多种轨迹(包括圆、螺旋、马鞍、圆线等)锥束CT扫描.采用一般轨迹下的基于弦线段和感兴趣区的BPF重建算法和圆轨迹下的FDK算法进行了图像重建.本文分别用头部和胸部体模研究了该系统的成像质量,最后采用Min/Max曲率流方法对重建后图像进行了去噪处理.结果表明采用该系统可以清晰地确定被扫描物体轮廓和骨性边界,为实现γ射线立体定向放疗设备在影像引导下进行病人自动摆位打下了基础.     

最小交叉熵图像重建算法

CT技术通过扫描和图像重建算法,获取被检物场断层图像.由于具有非侵入性、可视化等特点,该技术在工业领域获得广泛应用.为了提高CT系统重建图像的分辨率,提出一种信息扩充策略,并以此为基础采用两种最小交叉熵算法--MAP和SMART,对多相流CT系统进行图像重建.与传统ART算法相比,最小交叉熵算法有效提高了重建图像的分辨率,减少重构图像伪影.仿真和实验结果表明,基于信息扩充的SMART算法不仅改进了重建图像质量,而且提高了实时性.     

用IDL实现基于CT图像的三维表面重建

利用计算机断层(CT)图像进行人体组织三维重建,在医学、人体科学等领域拥有非常广阔的应用前景.IDL是近年来被广泛应用于医学图像处理的交互式数据语言.本文结合一组CT图像,介绍了一种用IDL语言实现CT图像形态学边缘检测、轮廓提取和三维表面重建的方法.并采用IDL中事件驱动的程序结构,设计了三维可视化程序.     

锥束XCT重建算法的实现

计算机断层成像(CT)是一门用来获取观测目标断层图像的技术,它广泛地应用于医疗诊断和工业无损检测等领域.与CT系统其他部分比,重建算法是其核心,本文实现了锥束CT重建的三种算法:FDK算法、Katsev-ich算法和EM算法,并对这三种算法进行了比较研究.     

工业CT断层图像缺陷检测的可视化方法研究

针对工业CT断层图像缺陷检测中的传统二维图像处理方法,提出了将三维可视化技术应用于二维灰度图像缺陷检测领域的算法流程.应用该算法流程,系统能够充分利用CT断层灰度图像信息,获得清晰的三维视觉效果,从而显著增强了系统检测缺陷的能力.在大型工业CT图像重建与检查分系统中采用该算法流程取得了较为理想的效果.     

CT特征重建技术研究

传统的CT重建技术在检测物体内部细小缺陷时,具有噪声难以滤除、分辨率低、对比度差等特点,滤波器设计和实现具有难度.文中提出一种特征CT重建技术,能有效改善上述缺陷,它是以突现构件特征为目的的CT重建算法,重建图像的目的不是达到整体图像质量最好,而是从突现重建图像特征出发,达到重建图像作用.文中首先介绍了二维及三维特征CT重建算法理论,并通过详细分析、实验结果与参数计算的对比,验证了特征CT重建方法在高频信息、抗噪能力、滤波器设计及实现速度方面的明显优势.     

基于Access的CT医学图像管理系统的关键技术研究

本文利用Access在Visual C++2005平台上开发出了CT医学图像管理系统。首先提取了系列CT图片的文件信息,与此同时提取了文件所在的地址—并导入数据库。从而通过对图像信息的管理实现了对图片的管理,并通过双击数据表中的元素读取序列图像,从而使其成为了医学图像处理系统一部分。在此基础上实现了模糊查询和无重复批量添加,让管理系统更高效、更具人性化。     

一种基于工业CT的航空发动机涡轮叶片生产检测系统关键技术研究

基于工业CT的航空发动机涡轮叶片无损检测系统能对涡轮叶片进行无损、准确、高效和全方位的检测.检测系统软件使用叶片的CT切片图像建立叶片的三维数字样品模型,基于此模型进行叶片的尺寸检测、表面轮廓度偏差分析、壁厚分析以及铸造缺陷分析,给出最终的检测报告.主要研究与实现了叶片数字样品模型生成、表面轮廓度偏差分析和壁厚分析等检测系统软件中的关键技术,使用实际的叶片CT扫描数据进行了验证.     

CT图像表面重建技术中的边缘轮廓提取方法

论述了 CT图像表面重建技术中的边缘轮廓提取方法。采用该方法 ,得到了 CT图像的截面数据 ,进而利用CAD软件实现了 CT图像表面的三维重建。最后给出了儿童股骨三维表面重建的实例     

基于改进MC算法的DICOM格式CT图像三维重建

保证MC算法所抽取等值面的拓扑正确并作有效实现是医学三维应用的关键技术。本文对MC算法的内部拓扑歧义判定方法作了改进,使其更为简单直观,并以此为基础开发了CT序列图像三维重建系统。系统读入D ICOM格式的CT图像数据,封装成由立方体单元组成的规则体数据,用改进的MC算法抽取等值面,得到三角网格模型,为后续基于三角网格的医用修复体设计研究打好了基础。     

基子CT图像快速成型数据的构建方法

本文针对医学CT图像数据,提出了由CT图像构建快速成型数据的建模方法,确定了CT图像处理方案,即通过对断层图像的预处理、滤波处理、数据提取,生成断层图像轮廓,继而通过对轮廓优化和轮廓冗余数据去除,得到用于三维重建的二维轮廓数据,并在此基础上构造出可直接用于快速原型制造的三维STL数字模型.本文所提出的方法能够大大提高快速医学模型的构建速度.     

定做式人工髋关节设计与加工中股骨轮廓提取方法

本文提出在设计定做式人工髋关节时使用的一种股骨ＣＴ片轮廓提取方法。采用本文论述的轮廓提取方法，作者得到了股骨的截面数据，并从而利用ＣＡＤ软件进行了股骨的三维重建，并在快速原型设备上得到了股骨的实体。     

Three-dimensional human body model reconstruction and manufacturing from CT medical image data using a heterogeneous implicit solid based approach

This paper presents a simple and effective method for reconstructing 3D bio-CAD models from a sequence of computer tomography (CT) medical image data. In this work, a heterogeneous implicit solid representation method is proposed to describe a heterogeneous model of the human body. The use of implicit solid as a basis for 3D bio-CAD models facilitates the robustness and simplification of the process for converting CT images to a 3D bio-CAD model. An almost perfect 3D bio-CAD model is achieved from implicit solid interpolation combined with domain decomposition. The implicit solid is defined by a radial basis function which is a continuous scalar-value function over the domain R ³. The generated solid consists of the set of all points at which this scalar function value is the Houndsfield unit (HU) value obtained from the CT image. CT images of human bone were used as the case studies for the reconstruction of the 3D solid model from CT scan data. Experimental results show that the proposed method has the potential to represent internal human body details accurately and efficiently suitable for rapid prototyping, finite element analysis, and tissue engineering.     

A comparison of 3D cone-beam Computed Tomography (CT) image reconstruction performance on homogeneous multi-core processor and on other processors

Computed Tomography (CT) has become an important noninvasive tool in diagnostic medicine. In fact, the use of cone-beam CT is growing in the clinical area due to its ability to provide 3D volumetric information. This study aims to parallelize an analytical 3D image reconstruction algorithm and then implement it on a commercial homogeneous multi-core processor. It is indicated from our results that the homogeneous multi-core processor actually achieved faster reconstruction than the heterogeneous processor-based or the FPGA-based implementation. Our results demonstrated that the shared cache mechanism associated with the homogeneous processor would represent a significant benefit to performing high-speed CT reconstruction or other High Performance Computing (HPC) applications. In addition, while the Graphic Processing Unit (GPU) is considered the most powerful processor nowadays, our experimental results further indicated that the joint use of the multi-core CPU and GPU could enhance the processing power as well as improve the computational efficiency.     

激光等离子体三维重建迭代方法研究

利用CT技术,采用乘代数重建法(MART)和加代数重建法(ART),编制出三维图像重建程序CT3D,通过对“星光Ⅱ”装置的激光等离子体进行X光针孔成像的五个方位,对三维重建问题进行数值模拟,计算结果表明MART比ART的重建精度高,能满足诊断误差δI/I小于10%的要求。     

Image reconstruction from sparse data in synchrotron-radiation-based microtomography

Synchrotron-radiation-based microcomputed-tomography (SR-μCT) is a powerful tool for yielding 3D structural information of high spatial and contrast resolution about a specimen preserved in its natural state. A large number of projection views are required currently for yielding SR-μCT images by use of existing algorithms without significant artifacts. When a wet biological specimen is imaged, synchrotron x-ray radiation from a large number of projection views can result in significant structural deformation within the specimen. A possible approach to reducing imaging time and specimen deformation is to decrease the number of projection views. In the work, using reconstruction algorithms developed recently for medical computed tomography (CT), we investigate and demonstrate image reconstruction from sparse-view data acquired in SR-μCT. Numerical results of our study suggest that images of practical value can be obtained from data acquired at a number of projection views significantly lower than those used currently in a typical SR-μCT imaging experiment.     

The 3D CT reconstruction algorithm to directly reconstruct multi-characteristic based on EMD

In the traditional three-dimensional CT reconstruction algorithms, high-frequency characteristics are difficult to obtain, and the noise is difficult to filter. In addition to, the reconstruction purpose is of diversification, and the three-dimensional filter to extract feature is more difficult to design and implement. Based on the characteristics of three-dimensional reconstruction algorithm and the RADON transform, a 3D CT reconstruction method to directly reconstruct multi-characteristic based on EMD was proposed and derived from the theoretical possibility and feasibility. EMD algorithm could firstly be used to decompose projection image before the reconstruction, and we could combine different IMF components to achieve a variety of feature, then use three-dimensional reconstruction algorithm to directly reconstruct the characteristics. The experimental results showed that the algorithm can better highlight a variety of useful information, simplify the filter design, and is of a certain practicability.