基于VT K 的D IC OM 医学图像三维重建研究

医学图像三维重建技术利用二维医学图像序列重建出三维模型,为医生提供直观、全面、准确的病灶和正常组织信息．是当今医学影像领域研究的热点之一。VTK是国际上广泛应用的可视化工具包,具有优秀的架构和运行机制。本文研究了DICOM3．0标准,提出了正确解读DICOM医学图像的方法;深入VTK内部机制,解决了VTK和DICOM医学图像读取模块间的数据接口问题;在三维重建过程中,为解决数据量巨大、成像时间漫长、阶梯效应、交互性不强等问题,重点剖析了VTK的数据处理机制。并给出相关优化方法。实验结果表明本文提出的解决方案和优化方法实用可靠,为进一步开发医学三雏图形系统打下了基础。     

基于VTK和MFC的医学图像三维重建研究与实现

VTK是医学可视化领域的主流工具,MFC是Windows平台下的应用程序框架。尝试将两者进行结合编程,以实现二维医学图像的三维重建。实现医学图像三维重建的主要方法是面绘制和体绘制。将利用多组医学图像数据进行三维重建研究,其中面绘制用移动立方体法,体绘制用光线投射法、最大密度投影法和合成体绘制法实现。最后比较两种绘制技术的结果并讨论了它们的特点。结果表明,VTK作为一种图像处理和三维可视化工具其功能是十分强大的。     

活体细胞三维图像科学可视化方法的研究

科学可视化是指运用计算机图形学和图像处理技术,将科学计算过程中或者是计算结果的数据转换为图形或图像,在屏幕上显示出来并进行交互式处理的理论技术或方法。介绍了用反卷积荧光显微成像技术获得活体大鼠胰腺B细胞三维图像及对其进行科学可视化的主要过程和两种常用可视化算法,并运用这两种方法对所得到的三维图像进行处理以分析和研究细胞内分泌囊泡的空间分布。结果显示,当仅观察细胞三维图像的二维切片时,三维图像中的某些重要信息会被忽略,而使用科学可视化方法则可以从三维角度直观观察活体细胞内分泌囊泡的空间分布,并且可以观察到分泌囊泡的释放趋势和整体分布,从而为细胞生物学研究提供重要的信息。     

脑室系统可视化研究在医学影像学教学培训中的应用

脑室系统疾病的诊断主要有赖于CT、MRI检查,掌握脑室系统的断层解剖学知识是认识正常和进行疾病诊断的基础.本文利用中国可视化人体中颅脑薄层连续断层图像,运用虚拟断层切割技术和三维重建技术,建立了脑室系统三维可视化模型.脑室系统可视化模型将断层解剖学与整体解剖相衔接,将横断、矢状与冠状位图像相结合,有助于培养学生的空间思维能力及建立脑室系统结构的三维立体概念,在临床医学影像学教学培训中取得了良好的教学效果.     

一种新型的基于图像的DNA序列可视化模型

传统的DNA序列可视化模型局限于短DNA序列的可视化,并且缺乏对可视化图形的通用分析方法。因此,文章提出了一种基于图像的DNA序列可视化模型,这种模型通过将一维的DNA序列转换为二维的256色的灰度图像,可以实现长DNA序列的可视化,具有很高的空间紧密性。借助成熟的图像处理方法来分析DNA可视化图像,可以获取原始DNA序列的规模、4种不同碱基的分布、无序程度等重要信息。通过比较不同DNA序列的可视化图像,可以获取这些序列的相似性信息。     

东亚飞蝗雄性生殖系统组织结构观察及三维可视化数字模型

本文研究东亚飞蝗Locusta migratoria manilensis(Meyen)雄性生殖系统组织解剖结构及三维可视化数字模型的构建。采用石蜡切片技术对东亚飞蝗进行组织切片,脱水、透明、HE染色和拍照;并应用冰冻切片技术将冰冻包埋剂包埋后的飞蝗雄性个体进行连续切片,进行截面图像信息采集,建立数据集;通过Photoshop、Image-Pro Plus(IPP)软件对雄性生殖器官截面图像进行分割、处理、序列化和三维重建。通过试验观察分析东亚飞蝗雄性生殖器官精巢、附腺、输精管、精球囊和射精囊及交配器的组织构造;并成功构建了飞蝗雄性生殖系统的三维结构可视化数字模型。该模型可以任意旋转,能从不同角度观察,该试验为研究和教学提供了理论基础。     

冷冻电镜密度图可视化软件VAT4M

基于冷冻电镜三维密度图的特征分析,研究开发了冷冻电镜密度图可视化软件VAT4M(Visual Analysis Tools for Macro-Molecule Map and Model),实现了对三维冷冻电镜密度图的可视化分析,其主要功能包括密度图和分子模型的可视化、密度图的分割和晶体结构在密度图中的匹配。在可视化方面,在实现等值面可视化方法的同时还实现了体绘制可视化模式。对于结构分析,VAT4M提供了自动分割工具,和所见即所得的分割浏览器。同时,VAT4M还提供了极值吸收法与梯度法相结合的自动匹配方法,而且,对于具有对称性的密度图,可根据一个亚基的匹配结果,迅速得到其准原子模型。最后给出了若干应用实例。实验表明,本平台对冷冻电镜密度数据具有良好的可视与分析功能。     

三维超声心脏图像的模糊聚类分割

采用三维超声心动图对小儿先天性心脏病进行诊断与治疗能达到比传统二维超声心动图更直观的效果。然而由于超声图像质量较差,三维超声心动图的可视化效果往往无法达到医生的要求。本文对三维超声心脏图像进行分割,以改进超声图像的可视化效果,并为参数提取等提供基础。首先采用快速的模糊c均值聚类得到初始分割结果;然后利用图像多分辨率技术进行修正;接着结合图像的对比度进行进一步的分割;最后,把处理后的图像用绘制的方法显示出来。本文的结果对超声图像的可视化效果有一定的改善.     

乳腺三维超声成像的文献计量和可视化分析*

目的:研究乳腺三维超声成像领域的发展态势并识别研究热点。方法:本研究选取PubMed数据库中乳腺三维超声成像领域的论文为研究对象,采用文献计量学方法,结合可视化分析工具,从论文数量、生命周期、国家/地区分布及合作、机构分布及合作、研究热点等多个角度对乳腺三维超声成像领域进行研究。结果:乳腺三维超声成像领域共发表论文213篇;25个国家/地区在该领域开展研究,其中美国发文量全球排名第一位;全球有100多个机构开展研究,主要以医院和大学为主;识别出研究热点有4个,分别是:乳腺肿瘤的三维弹性成像研究,乳腺X线图像的计算机辅助诊断方法研究,乳腺癌的磁共振成像诊断研究,乳腺肿瘤超声图像特征的算法研究。结论:乳腺三维超声成像领域近几年发展较快,其研究热点主要围绕乳腺癌诊断的相关研究。     

小麦根系三维形态建模及可视化

作物三维形态建模和可视化技术是数字植物研究的重要组成部分,本文旨在构建基于形态特征参数的小麦根系三维形态模型,并实现小麦根系生长的可视化.基于小麦根系生长的可视化技术框架,首先构建了小麦根轴的三维显示模型,包括根轴生长模型、分枝几何模型和根轴曲线模型;然后结合根系拓扑结构,确定相应的图元,利用根系形态模型输出的形态特征参数,对整个小麦根系进行三维重构;最后基于OpenGL图形平台,综合纹理映射、光照渲染、碰撞检测等真实感处理手段,实现了小麦根系生长的三维可视化表达.结果表明：模型输出的根系真实感较强,能较好地实现不同品种、水分和氮素条件下小麦根系的三维可视化表达.研究结果为进一步建立完整的可视化小麦生长系统奠定了技术基础.     

daime, a novel image analysis program for microbial ecology and biofilm research

Combinations of microscopy and molecular techniques to detect, identify and characterize microorganisms in environmental and medical samples are widely used in microbial ecology and biofilm research. The scope of these methods, which include fluorescence in situ hybridization (FISH) with rRNA-targeted probes, is extended by digital image analysis routines that extract from micrographs important quantitative data. Here we introduce daime (digital image analysis in microbial ecology), a new computer program integrating 2-D and 3-D image analysis and visualization functionality, which has previously not been available in a single open-source software package. For example, daime automatically finds 2-D and 3-D objects in images and confocal image stacks, and offers special functions for quantifying microbial populations and evaluating new FISH probes. A novel feature is the quantification of spatial localization patterns of microorganisms in complex samples like biofilms. In combination with '3D-FISH', which preserves the 3-D structure of samples, this stereological technique was applied in a proof of principle experiment on activated sludge and provided quantitative evidence that functionally linked ammonia and nitrite oxidizers cluster together in their habitat. This image analysis method complements recent molecular techniques for analysing structure-function relationships in microbial communities and will help to characterize symbiotic interactions among microorganisms.     

Visualization and correction of automated segmentation,tracking and lineaging from 5-D stem cell image sequences

Background

Neural stem cells are motile and proliferative cells that undergo mitosis, dividing to produce daughter cells and ultimately generating differentiated neurons and glia. Understanding the mechanisms controlling neural stem cell proliferation and differentiation will play a key role in the emerging fields of regenerative medicine and cancer therapeutics. Stem cell studies in vitro from 2-D image data are well established. Visualizing and analyzing large three dimensional images of intact tissue is a challenging task. It becomes more difficult as the dimensionality of the image data increases to include time and additional fluorescence channels. There is a pressing need for 5-D image analysis and visualization tools to study cellular dynamics in the intact niche and to quantify the role that environmental factors play in determining cell fate.

Results

We present an application that integrates visualization and quantitative analysis of 5-D (x,y,z,t,channel) and large montage confocal fluorescence microscopy images. The image sequences show stem cells together with blood vessels, enabling quantification of the dynamic behaviors of stem cells in relation to their vascular niche, with applications in developmental and cancer biology. Our application automatically segments, tracks, and lineages the image sequence data and then allows the user to view and edit the results of automated algorithms in a stereoscopic 3-D window while simultaneously viewing the stem cell lineage tree in a 2-D window. Using the GPU to store and render the image sequence data enables a hybrid computational approach. An inference-based approach utilizing user-provided edits to automatically correct related mistakes executes interactively on the system CPU while the GPU handles 3-D visualization tasks.

Conclusions

By exploiting commodity computer gaming hardware, we have developed an application that can be run in the laboratory to facilitate rapid iteration through biological experiments. We combine unsupervised image analysis algorithms with an interactive visualization of the results. Our validation interface allows for each data set to be corrected to 100% accuracy, ensuring that downstream data analysis is accurate and verifiable. Our tool is the first to combine all of these aspects, leveraging the synergies obtained by utilizing validation information from stereo visualization to improve the low level image processing tasks.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-328) contains supplementary material, which is available to authorized users.     

Simple fractal method of assessment of histological images for application in medical diagnostics

We propose new method of assessment of histological images for medical diagnostics. 2-D image is preprocessed to form 1-D landscapes or 1-D signature of the image contour and then their complexity is analyzed using Higuchi's fractal dimension method. The method may have broad medical application, from choosing implant materials to differentiation between benign masses and malignant breast tumors.     

How Accurate Are the Fusion of Cone-Beam CT and 3-D Stereophotographic Images?

Background

Cone-beam Computed Tomography (CBCT) and stereophotography are two of the latest imaging modalities available for three-dimensional (3-D) visualization of craniofacial structures. However, CBCT provides only limited information on surface texture. This can be overcome by combining the bone images derived from CBCT with 3-D photographs. The objectives of this study were 1) to evaluate the feasibility of integrating 3-D Photos and CBCT images 2) to assess degree of error that may occur during the above processes and 3) to identify facial regions that would be most appropriate for 3-D image registration.

Methodology

CBCT scans and stereophotographic images from 29 patients were used for this study. Two 3-D images corresponding to the skin and bone were extracted from the CBCT data. The 3-D photo was superimposed on the CBCT skin image using relatively immobile areas of the face as a reference. 3-D colour maps were used to assess the accuracy of superimposition were distance differences between the CBCT and 3-D photo were recorded as the signed average and the Root Mean Square (RMS) error.

Principal Findings:

The signed average and RMS of the distance differences between the registered surfaces were −0.018 (±0.129) mm and 0.739 (±0.239) mm respectively. The most errors were found in areas surrounding the lips and the eyes, while minimal errors were noted in the forehead, root of the nose and zygoma.

Conclusions

CBCT and 3-D photographic data can be successfully fused with minimal errors. When compared to RMS, the signed average was found to under-represent the registration error. The virtual 3-D composite craniofacial models permit concurrent assessment of bone and soft tissues during diagnosis and treatment planning.     

A microcomputer based system for three-dimensional reconstructions from tomographic or histologic sections

The reconstructions of three-dimensional (3-D) objects from serial two-dimensional (2-D) images can contribute to the understanding of many biologic structures, from organelles to organs and tissues. The 3-D reconstruction of sections can be divided into several major tasks: image acquisition, alignment of slices, internal object definition, object reconstruction and rotation of the completed image. A fast, versatile, interactive system was devised for the reconstruction of 3-D objects from serial 2-D images using a low-cost microcomputer, original programs and commercial software. The system allows reconstruction from any serial images, e.g., electron micrographs, histologic sections or computed tomograms. A photographic image or a microscopic field is acquired into the computer memory using a video digitizer. Slices are superimposed and aligned to each other using an operator-interactive program. A contour-(edge-) finding algorithm isolates an object of interest from the background image by "subtraction" of the image from an overlaid, slightly shifted identical image. Contours for each slice are input to a reconstruction procedure, which calculates the x, y and z coordinates of every point in a slice and the thickness and number of slices. It then calculates the illumination for every point using a given point source of light and an intensity-fading coefficient. Finally, the points are represented by cubes to provide dimension and reflective surfaces. A cube of appropriate shade and color represents in 2-D the equivalent of a 3-D object; this results in a very effective 3-D image. The reconstruction is rotated by recalculating the positions of every point defining the object and rebuilding the image.(ABSTRACT TRUNCATED AT 250 WORDS)     

A statistical approach to computer processing of cryo-electron microscope images: virion classification and 3-D reconstruction

The scattering density of the virus is represented as a truncated weighted sum of orthonormal basis functions in spherical coordinates, where the angular dependence of each basis function has icosahedral symmetry. A statistical model of the image formation process is proposed and the maximum likelihood estimation method computed by an expectation-maximization algorithm is used to estimate the weights in the sum and thereby compute a 3-D reconstruction of the virus particle. If multiple types of virus particle are represented in the boxed images then multiple 3-D reconstructions are computed simultaneously without first requiring that the type of particle shown in each boxed image be determined. Examples of the procedure are described for viruses with known structure: (1). 3-D reconstruction of Flockhouse Virus from experimental images, (2). 3-D reconstruction of the capsid of Nudaurelia Omega Capensis Virus from synthetic images, and (3). 3-D reconstruction of both the capsid and the procapsid of Nudaurelia Omega Capensis Virus from a mixture of unclassified synthetic images.     

基于小波变换的医学图像编码方法

高分辨率的医学图像具有很大的信息量,影响了整个数字化的远程医疗系统的实时性,因此必须在保证不丢失关键诊断信息的前提下,对医学图像进行必要的压缩。本文提出了在给定小波基下,基于二维小波分解和重构的快速压缩方法。该方法使用了向量量化技术并采用LBG算法设计码本。实验结果证明,采用该方法可获得较高的压缩比和符合诊断要求的压缩图像。