JPEG2000压缩算法及其在医学图像DICOM格式中的实现

本文描述了在医学图像DICOM格式中实现JPEG2000压缩算法的编程思路和方法。提供了部分VC＋＋代码,对关键函数进行了较详细的注解,并对两种图像压缩格式进行了比较,给出了一个详细的实验结果。     

常用医学图像“局部显微镜”程序的研究

在医学临床和科学研究中,常常需要将图像的某个感兴趣区域(ROI)进行放大显示,以便清晰地观察图像的细节.为了实现这一目标,采用IDL语言(Interactive Data Language)编写了应用程序,从而实现了医学图像“局部显微镜”的功能.一系列实验表明:对于各种常用的医学图像类型(灰度图像、RGB图像、DICOM图像等),程序均能较好地实现放大显示的功能.此外,该程序还具有人机交互性强、可移植性高等优点.     

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。     

基于最大熵和改进PCNN的医学图像自动分割算法研究与实现

本文提出了基于最大熵和改进的PCNN(Pulse Coupled Neural Network)相结合的新方法,采用最大熵确定PCNN网络的循环迭代次数.提出的方法无需考虑PCNN参数的选择,可有效的自动分割各种医学图像,同时利用最大熵得到最优分割结果.该方法对于PCNN理论在医学图像分割领域的应用有着重要的意义.     

医学图像融合技术的研究

利用图像融合技术,将不同模态的医学图像有机地结合在一起,可以充分利用各种医学图像的优点,为临床诊断和治疗提供帮助。本文主要介绍了医学图像融合技术的基本概念、发展情况、常用方法及面临的困难等,并对医学图像的研究前景作了预测。     

基于PET医学图像边缘检测算法的研究

目的:边缘检测在图像处理中至关重要,可被广泛应用于目标区域识别、区域形状检测、图像分割等图像分析领域。边缘是图像中不平稳现象和不规则结构的重要表现,往往携带着图像中的大量信息,并给出图像轮廓。在医学图像三维显示技术中,为了更精确的临床判别需要得到单像素的清晰轮廓,因此我们提出一种新的边缘检测算法。方法:在传统的小波边缘检测的基础上,提出了一种新的边缘算法,即基于小波极大值边缘检测算法,应用模糊算法构造相应的隶属函数,再对得到的极大值进一步筛选。结果:将该算法应用到医学图像中,最终可以得到较清楚的单像素边缘轮廓,实验结果证明了该算法的可行性。结论:运用这种算法处理过的医学图像边缘锐化更好,更清晰,能够为肿瘤的早期识别提供依据,满足医学影像识别的需要。     

基于Snake模型的医学图像分割

基于Snake模型的图像分割技术是近年来图像处理领域的研究热点之一。Snake模型承载上层先验知识并融合了图像的底层特征,针对医学图像的特殊性,能有效地应用于医学图像的分割中。本文对各种基于Snake模型的改进算法和进化模型进行了研究,并重点梳理了最新的研究成果,以利于把握基于Snake模型的医学图像分割方法的脉络和发展方向。     

基于小波分析的医学图像的处理

医学图像的好坏直接影响着医生对病情的诊断和治疗,因此利用数字图像处理等技术对医学图像进行有效的处理,已成为医学图像处理研究和开发的一大热点.小波分析是对傅立叶变换的继承和发展,在医学影像领域有着广阔的应用前景.介绍了二维离散小波变换的一般形式,在图像分解的基础上,利用小波分析对医学图像进行去噪和增强处理,能够有效的改善图像质量,有利于医生对病情的诊断和治疗.     

探讨医学图像库的新进展

随着数字化医疗设备如CT、MR、DSA、DR在临床医学诊断中的大量采用,以及计算机技术在医院的广泛应用,医学影像数据正在里海量增长,现有的存储、图像处理及管理方式面临着巨大的挑战。网络医学图像库的出现,给医学图像库发展提供了条件和基础。而计算机网络的发展趋势是：开放、集成、高性能和智能化。它们渗透到网络自身、网络服务和网络应用的各个层次。基于医院现有影像数据系统,建立网络应用环境,来满足医学图像库发展的需要,为解决数字医学图像库所面临的问题提供一条很好的技术思路。     

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。     

Digital Imaging and Communications in Medicine (DICOM) information conversion procedure for SUV calculation of PET scanners with different DICOM header information

PurposeIn nuclear medicine, the standardized uptake value (SUV) obtained using positron emission tomography with 2-deoxy-2-fluoro-D-glucose (FDG-PET) is widely used as a semi-quantitative diagnosis factor. We found that the header file of the Philips Allegro PET scanner using the Digital Imaging and Communications in Medicine (DICOM) standard was stored differently than with other scanners. Thus, the purpose of this study was to develop a DICOM header information conversion program to ensure compatibility between Allegro and other equipment.Methods and resultsThe NEMA IEC Body phantom was scanned using the Allegro PET scanner. We conducted measurements and performed calculations by using commercial software and the proposed self-developed program, respectively, to compare the SUVs by using conversion data. The program consists of three parts: an input part that can load data regardless of the number of DICOM images, and conversion and output parts that can be used to convert the DICOM header information and store it in the order of slices. The results of the calculation are in good agreement with the data measured at 12 circular regions of interest. The percent difference was lower than the 20%.ConclusionIn conclusion, this study suggested a simple and convenient method to solve the incompatibility through conversion of the DICOM header information. This study thus provides physicians more accurate information for diagnosis and treatment.     

Biological Image Segmentation Using Region-Scalable Fitting Energy with B-Spline Level Set Implementation and Watershed

ObjectivesImage segmentation plays an important role in the analysis and understanding of the cellular process. However, this task becomes difficult when there is intensity inhomogeneity between regions, and it is more challenging in the presence of the noise and clustered cells. The goal of the paper is propose an image segmentation framework that tackles the above cited problems.Material and methodsA new method composed of two steps is proposed: First, segment the image using B-spline level set with Region-Scalable Fitting (RSF) active contour model, second apply the Watershed algorithm based on new object markers to refine the segmentation and separate clustered cells. The major contributions of the paper are: 1) Use of a continuous formulation of the level set in the B-spline basis, 2) Develop the energy function and its derivative by introducing the RSF model to deal with intensity inhomogeneity, 3) For the Watershed, propose a relevant choice of markers that considers the cell properties.ResultsExperimental results are performed on widely used synthetic images, in addition to simulated and real biological images, without and with additive noise. They attest the high quality of segmentation of the proposed method in terms of quantitative and qualitative evaluation.ConclusionThe proposed method is able to tackle many difficulties at the same time: overlapped intensities, noise, different cell sizes and clustered cells. It provides an efficient tool for image segmentation especially biological ones.     

容积减影成像计算机自动化技术与实现

探讨在PC机上对容积CT灌注（CTP）源影像全自动生成减影CTP源影像的方法。首先在WindowsXP操作系统中使用Matlab,对4层螺旋CTP源影像进行DICOM文件格式解析,获得CT成像设备的球管每转一周扫描层数及容积减影方法需要的其它参数信息,然后经过容积的CT值集合读、容积的CT值集合减以及容积的CT值集合写等几个步骤,生成减影CTP源影像的DICOM文件序列。使用该容积减影方法得到的减影CTP源影像,在定性肉眼观察和定量CT值矩阵比对上,与使用CT影像工作站上的减影软件手工逐层半自动减影得到的结果类同。容积减影方法实现了容积CTP源影像的自动化减影处理与成像,为最终形成一个一站式的减影CTP软件奠定了基础。     

Fast and Accurate Registration of the Proximal Femurs in Bilateral Hip Joint Images by Using the Random Sub-Sample Points

Background and ObjectiveAs is known, point clouds representing the objects are frequently used in object registration. Although the objects can be registered by using all the points in the corresponding point clouds of the objects, the registration process can also be achieved with a smaller number of the landmark points selected from the entire point clouds of the objects. This paper introduces a research study focusing on the fast and accurate rigid registration of the bilateral proximal femurs in bilateral hip joint images by using the random sub-sample points. For this purpose, Random Point Sub-sampling (RPS) was analyzed and the reduced point sets were used for an accurate registration of the bilateral proximal femurs in coronal hip joint magnetic resonance imaging (MRI) slices.MethodsIn registration, bilateral proximal femurs in MRI slices were registered rigidly by performing a process consisting of three main phases named as MR image preprocessing, proximal femur registration over the random sub-sample points and MR image postprocessing. In the stage of the MR image preprocessing, segmentation maps of the bilateral proximal femurs are obtained as region of interest (RoI) images from the entire MRI slices and then, the edge maps of the segmented proximal femurs are extracted. In the registration phase, the edge maps describing the proximal femur surfaces are represented as point clouds initially. Thereafter, the RPS is performed on the proximal femur point clouds and the number of points representing the proximal femurs is reduced at different ratios. For the registration of the point clouds, the Iterative Closest Point (ICP) algorithm is performed on the reduced sets of points. Finally, the registration procedures are completed by performing MR image postprocessing on the registered proximal femur images.ResultsIn performance evaluation tests performed on healthy and pathological proximal femurs in 13 bilateral coronal hip joint MRI slices of 13 Legg-Calve-Perthes disease (LCPD) patients, bilateral proximal femurs were successfully registered with very small error rates by using the reduced set of points obtained via the RPS and promising results were achieved. The minimum error rate was observed at RPS rate of 30% as the value of 0.41 (±0.31)% on all over the bilateral proximal femurs evaluated. When the range of RPS rate of 20-30% is considered as the reference, the elapsed time in registration can be reduced by almost 30-40% compared to the case where all the proximal femur points were included in registration. Additionally, it was observed that the RPS rate should be selected as at least 25% to achieve a successful registration with an error rate below 1%.ConclusionIt was concluded from the observed results that a more successful and faster registration can be accomplished by selecting fewer points randomly from the point sets of proximal femurs instead of using all the points describing the proximal femurs. Not only an accurate registration with low error rates was performed, but also a faster registration process was performed by means of the limited number of points that are sub-sampled randomly from the whole point sets.     

农作物种质资源调查数据标准制定与共享

系统提取并分析了农作物种质资源普查数据、调查数据、评价数据和保存数据等数据信息,采用基于数据元技术方法制定了农作物种质资源调查数据标准和数据元目录;定义了种质资源调查数据集以及对象和属性的映射关系;给出了基于XML数据标准存储及交换策略。标准的制定使农作物种质资源调查在"数据层"上达到统一,规范了数据库构建,促进了农作物种质资源调查数据的整合和共享。     

脑脓肿与脑转移瘤的CT、M租诊断与鉴别诊断

目的：探索CT与MRI对脑脓肿及脑转移瘤的诊断及鉴别诊断价值。方法：对经病理及临床确诊的脑转移瘤及脑脓肿各20例,分别进行CT、MRI的平扫及增强扫描,对其影像表现进行比较分析,研究鉴别诊断的可能性。结果：脑脓肿多以全身或局部感染为首发症状,影像学表现病灶多为单发,平扫以囊性或囊实性表现为主,呈环状强化,壁薄,光滑,无壁结节。周围水肿以轻、中度片状水肿为主。脑转移瘤多以颅内压增高为首发症状,影像学表现多为多发,平扫以低、等密度为主,较小者呈结节状强化,边缘规则,较大者呈环状、花环状、结节状强化,壁厚薄不均,可见壁结节,周围大片状指状水肿。结论：脑脓肿及脑转移瘤具有不同的影像表现,CT及MRI具有较大的诊断意义。     

The Visual Orientation Strategies of Mantis religiosa and Empusa fasciata Reflect Differences in the Structure of Their Visual Surroundings

In the present study, peering behaviour, which is used to measure distance by the image motion caused by head movement, is examined in two types of mantid. Mantis religiosa inhabits a region of dense grass consisting of uniform, generally uniformly aligned, and closely spaced elements and executes slow, simple peering movements. In contrast, Empusa fasciata climbs about in open regions of shrubs and bushes which consist of irregular, variably aligned and variably spaced elements and it executes comparatively quick, complex peering movements. Hence, it seems that in these two species of mantid, the same orientation mechanism has been adapted to the unique structures of their visual surroundings. Apparently M. religiosa uses motion parallax and E. fasciata uses a combination of motion parallax and forward and backward movements (image expansion/contraction over time) to detect object distances.     

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.