结构光方法在荧光分子断层成像系统的三维轮廓重构中的应用

荧光分子断层成像系统需要获取成像物体的三维表面轮廓,用于荧光团浓度重建的前向模型,本文提出了基于结构光方法的成像物体的三维表面轮廓重构。首先利用8比特格雷码对图像进行编码,再将编码后的图像投射到成像对象,这时经成像物体的三维表面轮廓调制后的图像再通过二值化、解码、插值和轮廓重构等步骤最后输出三维表面轮廓。圆柱物体和小鼠实验表明,该方法可以较好地重构成像物体的三维表面轮廓,并且具有硬件系统简单、易实现等优点。     

利用数字几何技术重建个性化骨骼模型

背景:由于医学CT体数据存在各向异性的特点,导致CT序列图像重建网格模型时产生阶梯表面,从而影响后续的医学诊断。目的:利用数字几何处理技术重建个性化骨骼模型。方法:首先基于互信息的图像配准算法对骨骼CT序列图像进行配准,接着使用图像分割提取骨骼轮廓集并转化为三维点云,然后使用高斯加权的主成分分析方法估算点云法向量并对点云进行三边滤波去噪,最后对点云进行自适应圆球覆盖及网格化处理,完成个性化骨骼模型重建。结果与结论:文章所提的方法可以生成光顺的个性化骨骼表面网格模型,所形成的三角网格形状规则且自适应分布,可以为计算机辅助制造、有限元分析及3D打印提供准确的三维模型。     

用于荧光分子断层成像的小动物躯干部分三维表面轮廓重建研究

目的:基于CCD的荧光分子断层成像(FMT)近年来取得了快速发展,非接触式荧光分子断层成像技术(FMT)需要获取成像对象的三维表面轮廓,用于荧光团浓度重建的前向模型.方法:提出一种在白光条件下基于反投影法的三维轮廓提取方法,在获取360°的CCD照片后,滤波反投影重建断层,经过相应的图像平滑处理,得到轮廓边界,校准后重建出表面轮廓.结果:仿体实验和小动物实验结果表明,该方法具有毫米量级的重建精度.结论:该方法能够很好地重建躯干部分表面三维轮廓,较其他表面轮廓提取方法简单、实用,而且能够顺利地结合到荧光成像的工作流程中去,不需要单独成像,保证了整个成像过程的连续性.     

一种用于医学图像配准的图像外边界的提取方法

医学图像配准是医学图像融合的第一步,而基于图像边界的配准方法对刚性物体图像（如人头颅骨的CT、MRI图像）来讲是一种较好的配准方法。本文给出了一种医学图像外边界的提取方法,它能够快速、准确地提取出CT、MRI等图像的外边界,为用边界法进行图像配准提供了保证。     

基于物质灰度正态分布的CT断层图像匹配插值

基于医学CT断层图像中物质灰度呈正态分布的特性,提出一种新的插值算法。先分割CT断层图像,再为每个插值点搜索属于同种物质的最佳匹配点对,最后基于物质灰度呈正态分布特性获取插值权值,计算出插值点的灰度值。针对灰度值相差较大的匹配点对,传统的线性插值方法容易生成误差,新算法避免了这些插值点误差的产生。对于存在较多灰度值差异大的匹配点对的4组测试切片,测试结果表明,与匹配点对间传统的线性插值方法相比较,新算法的标记点均偏差平均降低29.55%,说明新算法具有良好的插值效果。     

儿科能谱CT扫描减少硬化伪影的基础探讨——与常规螺旋CT扫描对比

目的采用小模体研究儿科检查中能谱CT扫描减少硬化伪影的能力。方法采用直径100 mm圆柱形CT剂量指数(CTDI)的等效模体(相当于小儿头颅),模体内含有5个圆孔,其中1孔在模体中心,其余4孔对称分布在模体周围,呈十字形交叉状。分别在圆孔内放置2 mL硬塑料试管,试管内均充盈相同浓度的造影剂。将模体分别进行常规100 k Vp电压螺旋CT扫描及能谱CT的宝石能谱图像(GSI)模式扫描。在重建图像上5个对比剂点的两点中间分别找到8个感兴趣区(ROI)(内侧4个,外侧4个),分别测量8个ROI和背景点的CT值及标准差(s_a,s_(bg))。对比100 kVp常规CT扫描图像与能谱CT扫描中不同单能量图像的硬化伪影指数(AI)差异,并进行统计学分析。结果 100 kVp常规CT图像中,5个对比剂点的CT值为(1 640.0±14.3)Hu,8个ROI AI值为16.4±4.1。在能谱CT的GSI模式扫描中,获得40~140 ke V101幅单能量图像,图像中每个ROI AI值均随着能量值(ke V)的升高逐渐下降,并在69~77 ke V单能量图像上各个ROI的硬化伪影基本消除。在不同单能量图像中,内侧ROI AI值较外侧ROI AI值大,但变化趋势相同,内侧ROI AI值在77 ke V单能量图像为0.0±1.7,外侧ROI AI值在69 ke V单能量图像为0.0±0.8。结论物质密度越高,其在CT扫描中所产生的硬化伪影越大。在儿科的能谱CT扫描中选取适当的单能量图像能够消除硬化伪影的干扰,提高图像质量。     

一种计算机断层图像辅助的肾动态图像感兴趣区自动检测方法

肾小球滤过率(GFR)是评估肾脏功能的重要指标,可采用肾动态显像联合Gates法计算获得。针对GFR计算问题,本文提出一种计算机断层(CT)图像辅助的肾动态图像感兴趣区(ROI)自动检测方法,以实现客观准确的GFR计算。该方法首先获得CT冠状面投影图像与单光子发射计算机断层成像(SPECT)的增强合成图像,完成双模态图像配准后,采用改进的水平集方法实现肾脏ROI的自动检测并获取本底ROI,最后利用Gates法计算GFR值。经临床数据验证,该方法能够自动完成肾脏GFR值计算,所得结果与临床报告一致。该方法在消除人工勾画环节的同时,还能提高ROI检测的准确性和稳定性,尤其有利于肾功能严重受损时的GFR计算。     

用于CT和MRI图像的轮廓波变换双水印算法

目的：为解决CT与MRI图像版权侵权与恶意破坏问题,通过结合轮廓波变换与斑点检测技术,提出一种基于轮廓波变换自动选择感兴趣区域（ROI）的双水印算法。方法：该算法通过斑点检测与奇异值分解,选取医学图像轮廓波低频域与诊断最相关的位置作为ROI,在ROI生成零水印图像用于保护图像的完整性,并将ROI生成的零水印与版权水印共同嵌入图像的非感兴趣区域。结果：该双水印算法与其他双水印算法相比,载体医学图像遭受攻击后的不可见性有很大提升,结构相似度达到94%以上。结论：斑点检测轮廓波双水印算法对常规攻击与几何攻击具有较好的鲁棒性,且对于载体医学图像视觉质量有明显提升。     

傅立叶轮廓术在重建三维物体轮廓中的应用

随着荧光分子断层成像(FMT)技术中系统结构和重建算法的改进,FMT技术已经成为一种重要的生命医学研究手段。目前FMT算法都需要得到被测对象的三维表面轮廓作为边界约束条件。本文提出一种在蓝紫光条件下基于傅立叶变换轮廓术(FTP)方法,经图像处理、频谱分析及滤波后重构出FMT系统实验中物体的轮廓。实验结果表明,该方法具有毫米量级的重建精度。该方法能够很好地重建出物体表面轮廓,以及实时监控实验过程中物体的行为,保证了整个成像过程的对应性。此外,该法选用蓝紫光段,避免了对荧光成像的干扰。     

基于水平集稳健特征统计算法的脑肿瘤自动分割研究

目的:研究基于水平集的稳健特征统计算法在脑部CT图像上自动勾画肿瘤轮廓的方法。方法:选取种子点,通过稳健统计量描述种子点及其周围点对象的特征,基于水平集算法进行轮廓演化,确定肿瘤的边界。运用C++语言编程处理图像,得到肿瘤的分割结果。选用正确率、体素相对差异率、对称位置表面距离的均方根、对称位置的平均表面距离等指标评价肿瘤分割结果与医生勾画结果的一致性。结果:19例脑瘤患者的CT图像进行肿瘤勾画,均能自动准确勾画肿瘤轮廓。平均正确率为0.92,体素相对差异率为0.12,对称位置表面距离的均方根为0.25 mm,对称位置的平均表面距离为0.49 mm,各评价指标均优于区域增长算法。结论:基于水平集稳健特征统计的分割算法,可以实现肿瘤轮廓的自动勾画,结果准确可靠。     

A new framework of image reconstruction from fan beam projections

In this paper, we present a unified framework to reconstruct images for both fan beam and cone beam projections. The important feature of our theoretical framework is that it does not depend on the classical concept of the Radon transform at all. This property allows us to directly generalize the ideas and techniques developed in this paper to the cone beam reconstruction problem. In this paper, we extract such a framework from developing a new image reconstruction scheme from fan beam projections. Our new scheme also provides us new understanding of fan beam reconstruction problem. Our main results for the fan beam reconstruction are the following: First, we derive a general reconstruction scheme, in which the data sufficiency condition is transparently revealed by the reconstruction formula. Specifically, the data sufficiency condition for an accurate reconstruction of a region of interest (ROI) is that all the lines passing through the ROI must intersect the source trajectory at least once. Second, we further simplify the general reconstruction scheme by following three major steps of our new framework: (i) using symmetries of intermediate function; (ii) handling the data redundancy; (iii) changing discrete summation over the possible focal points into an integral along the source trajectory. After these steps, we obtain a new filtered backprojection algorithm. The key characteristic of this new algorithm is to take derivative of measured data with respect to the trajectory parameter. In practice, we can trade this derivative to some other continuous functions. In the configuration of a circular source trajectory with a third generation arc/collinear detector, we demonstrate how to remove the undesirable derivative of measured projection data. It results in a new algorithm for the sequential reconstruction of a ROI with a general normalized weighting function.     

颅底外面部分骨性标志三维坐标值及其意义

目的 :探讨测量颅底外面解剖结构三维空间坐标的方法并为临床应用提供相关数据。方法 :建立与颅底内面相统一的三维空间坐标系 ,在特制颅器上以 3 2个成年国人水平锯开颅骨标本为测量对象。结果 :测出了颅底外面骨性标志 2 1项共 3 4个测点的三维空间坐标值 ;可准确地测算出各测点在颅表各个方位的投影点和深度 ;根据坐标值和解析几何公式 ,还可推算出所有测点间连线 (线段 )的距离 (测距 )及其与三个基准坐标面的角度 (测角 )。结论 :明确了颅底外面各测点的空间位置和颅底内外两面任何测点间的位置关系 ,为颅底手术定位或放疗照射野等定位设计 ,提供了更为简便可靠的新方法。     

A Method for Assessing 3D Shape Variations of Fuzzy Regions and its Application on Human Bony Orbits

In complex orbital defects, typically the eye globe is retruded in a pathological position. This is associated with severe functional and cosmetic post-traumatic conditions. Characteristically, the posterior orbital floor and the medial wall of the bony orbit (=region of interest, ROI) is fractured where adequate reconstruction is crucial for a satisfactory surgical outcome but difficult to achieve. By introducing the concept of preshaped, navigated orbital implants, the repair of complex orbital fracture patterns could be significantly facilitated and improved. However, this ROI, delineated according to surgical criteria, cannot be defined by distinct anatomical landmarks because of the absence of reliable anatomical features. The determination of homologous surface points therefore remains a problem in such regions. The aim of this study was to provide a method for the assessment of the 3D shape of the ROI and of its variability, respectively. By aligning an anatomically determinable region that embeds the region of interest with a thin plate spline, transformation homology can be determined suitable for subsequent state-of-the-art shape analysis. First results of shape variations are illustrated and give hints into the future of optimized implant design.     

Two-dimensional iterative region-of-interest (ROI) reconstruction from truncated projection data

A small detector or limited gantry rotation angles may cause data truncation, in which case the entire object cannot be completely reconstructed. However, a small region of interest (ROI) may be recoverable in certain truncation situations. Two analytical methods have been proposed for exact ROI reconstruction. Here we evaluate the capability of ROI reconstruction using an maximum-likelihood expectation-maximization (ML-EM) method, which directly solves the inverse problem of the system equations. ROI reconstruction using the ML-EM method is compared with that using the two analytical methods. Comparisons are based on reconstructions of four specifically designed, computer-simulated truncation cases. In the simulation, each reconstructed ROI is coupled with its counterpart in the nontruncated case to evaluate the accuracy of the reconstructed ROI. We found that, (a) in two truncation situations the ROI can be reconstructed by both the analytical methods and the two-dimensional ML-EM method, but the ML-EM method may produce a larger ROI; (b) for a truncation case [Fig. 3(c)] that neither analytical algorithm is applicable, the ML-EM method provides a quantitative ROI reconstruction; and (c) for the well-known "interior" truncation problem, neither the analytical methods nor the ML-EM method can perform an exact ROI reconstruction, but the ML-EM method provides informative ROI images. We also propose an analysis using the truncated projection matrix and its Moore-Penrose inverse matrix which can help to determine the recoverable ROI using iterative methods for a given truncation situation.     

A simple derivation and analysis of a helical cone beam tomographic algorithm for long object imaging via a novel definition of region of interest

We derive and analyse a simple algorithm first proposed by Kudo et al (2001 Proc. 2001 Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine (Pacific Grove, CA) pp 7-10) for long object imaging from truncated helical cone beam data via a novel definition of region of interest (ROI). Our approach is based on the theory of short object imaging by Kudo et al (1998 Phys. Med. Biol. 43 2885-909). One of the key findings in their work is that filtering of the truncated projection can be divided into two parts: one, finite in the axial direction, results from ramp filtering the data within the Tam window. The other, infinite in the z direction, results from unbounded filtering of ray sums over PI lines only. We show that for an ROI defined by PI lines emanating from the initial and final source positions on a helical segment, the boundary data which would otherwise contaminate the reconstruction of the ROI can be completely excluded. This novel definition of the ROI leads to a simple algorithm for long object imaging. The overscan of the algorithm is analytically calculated and it is the same as that of the zero boundary method. The reconstructed ROI can be divided into two regions: one is minimally contaminated by the portion outside the ROI, while the other is reconstructed free of contamination. We validate the algorithm with a 3D Shepp-Logan phantom and a disc phantom.     

基于实时三维超声图像的二尖瓣环重建及运动分析

二尖瓣环的非平面特性对二尖瓣返流的超声诊断和二尖瓣环成形术的合理设计具有重要意义.基于心脏的实时三维超声图像,我们研究了一种对二尖瓣环三维重建及运动分析的方法.首先通过人机交互方式提取出二尖瓣环的特征点,并根据位置关系对特征点排序,然后利用非均匀有理B样条曲线建立二尖瓣环三维形态模型,并编程实现二尖瓣环的动态显示和运动分析.通过对20组病例分析,初步证明此方法所建模型较准确反映患者的二尖瓣环的运动,能满足二尖瓣环三维可视化和分析研究的需要.     

Null-space function estimation for the interior problem

In single-photon emission computed tomography (SPECT), projection data can be truncated when the camera's field of view is smaller than the object to be imaged. Using truncated projections to reconstruct a region of interest (ROI) is a reality we must face if small detectors are used. The truncated data result in an underdetermined system of imaging equations, which may lead to non-unique solutions. Data sampling and photon attenuation may also affect the solution uniqueness and stability. The uniqueness of the solutions in the ROI can be investigated by studying the null-space functions in the ROI. This paper uses an iterative algorithm to estimate the null-space image, to determine the sampling conditions under which a stable ROI reconstruction is possible with truncated data and to investigate whether attenuation can influence the ROI reconstruction bias. This iterative algorithm is validated by the singular value decomposition method. We show that if the ROI is sufficiently sampled, the null-space image is close to zero inside the ROI, and any almost-zero offset is insignificant in SPECT, because the noise is a much more dominating degradation factor.     

3D Medical Image Segmentation Based on Rough Set Theory

This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI（region of interest） when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions： positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.     

Region of interest motion compensation for PET image reconstruction

A motion-incorporated reconstruction (MIR) method for gated PET imaging has recently been developed by several authors to correct for respiratory motion artifacts in PET imaging. This method however relies on a motion map derived from images (4D PET or 4D CT) of the entire field of view (FOV). In this study we present a region of interest (ROI)-based extension to this method, whereby only the motion map of a user-defined ROI is required and motion incorporation during image reconstruction is solely performed within the ROI. A phantom study and an NCAT computer simulation study were performed to test the feasibility of this method. The phantom study showed that the ROI-based MIR produced results that are within 1.26% of those obtained by the full image-based MIR approach when using the same accurate motion information. The NCAT phantom study on the other hand, further verified that motion of features of interest in an image can be estimated more efficiently and potentially more accurately using the ROI-based approach. A reduction of motion estimation time from 450 s to 30 and 73 s was achieved for two different ROIs respectively. In addition, the ROI-based approach showed a reduction in registration error of 43% for one ROI, which effectively reduced quantification bias by 44% and 32% using mean and maximum voxel values, respectively.     

利用边缘和表面特征实现脑图像的自动配准

本文中我们使用基于CT、MR和PET图像等值特征表面的配准算法对多模医学图像进行了配准研究，在CT、MR和PET的原始图像中提取等值特征表面，进行图像的几何对准，并对结果进行初步评估，同时对该算法的稳健性，搜索最近点策略和采样策略进行了研究，结果表明；这种方法能够达到亚像素级的配准精度，是一种稳健、高精度、全自动的配准方法。