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.     

在医学图像DICOM格式中实现JPEG压缩算法

本文描述了在医学图像DICOM格式中实现JPEG压缩算法的编程思路和方法.文中提供了部分VC 代码,并对关键函数进行了较详细的注解,对同类工作具有参考价值.     

DICOM标准的语义扩充

医学图像数字成像和通信（Digital Imaging and Communicationsin Medicine，DICOM）标准是美国电气制造商联合会（NEMA）和美国放射学会（ACR）为了医学图像的存储和传输而制定的标准，在医学上得到广泛的应用。但该标准目前没有充分定义图像语义内容，从而使得实际中不能有效的实现DICOM的基于语义的应用。本文讨论了医学图像中的语义描述层次结构，概述了DICOM标准中对图像的描述方法并指出了该标准对图像语义内容描述的不足，给出了使用DICOM标准中私有属性对DICOM图像语义内容进行扩充的方法。     

Hi-PACS的结构及临床应用研究

目的 组建医院综合影像存储与传输系统Hi-PACS（hospital integrated picture archiving and communication system,是“第二代PACS”），探讨Hi-PACS的结构及其发展模式。方法 我们和高速以太网构建Hi-PACS的基础网络框架，把多个mini-PACS,D-PACS集合在一个系统中，各影像科室，临床科室通过该网互相连通，实现影像图像资料的共享。网络主干由光缆，交换机构成，各分支同100M集线器，双绞线，RJ45插头与影像设计构成星型拓扑结构。TCP，IP，DICOM协议。操作系统为Winodws9x/NT/Me/2000/XP,UNIX。建立Internet网站使影像图像进入广域网。使用软件把DICOM格式的图像转换成JPEG，GIF格式，用Dreamweaver,Flash,FrontPage制作网页，用Ws_FTP把网页传送到Internet网站。网址为http://www.imaging-nsmc.com.cn或http://cbyimage.myetang.com。结果 实现了数字化医学图像在Hi-PACS各模块间的传送，中心存储，激光胶片打印机共享，无胶片多媒体幻灯片和课件的制作，不同操作系统（UNIX和Windows NT/9x/Me/2000/XP)间的图像交流，不同格式(DICOM,JPEG,BMP,TIF,LWF,GIF,SWF,AVI)相互转换，兼容。进入Internet用于远程会诊，远程教育，远程放射学及献资料查阅。结论 Hi-PACS的建立方便了影像图像的管理及影像学临床与教学，科研工作，推动了数字化医院的变革。     

基于ITK读写DICOM医学图像文件

目的 介绍使用ITK读取DICOM文件文件头信息、访问像素数据以及存储DICOM文件的使用方法,以促进ITK在国内医学图像处理领域的普及应用。方法 使用itk：：ImageFileReader类和itk：：GDCMImageIO类对DICOM文件的文件头进行解析。介绍了使用图像迭代器访问图像像素的方法,熟悉C编程的研究人员快速访问像素数据的方法,及使用itk：：ImageFileWriter类进行图像写操作的方法。结果 使用本文的方法能够获取DICOM医学图像文件头中的医疗信息,读取像素数据,并以DICOM格式存储医学图像信息。结论 即使对DICOM标准和图像格式没有深入的了解,使用ITK也能方便地读写DICOM医学图像文件。     

基于DICOM标准的增强型体外反搏波形的压缩和存储

随着基于数字影像和通信(digital i maging and communications in medicine,DICOM)标准的体外反搏局域网系统和基于可扩展标记语言(extensible markuplanguage,XML)的远程体外反搏信息系统的建立和完善,体外反搏医学信息正逐步实现数字化的管理和共享。为了节省存储空间和提高传输效率,需要对长时间采集的反搏数据压缩并标准化存储。本文针对具有双通道采集、信号相关性强等特点的增强型体外反搏(enhanced external counterpulsation,EECP)数据设计了改进的模板匹配和快速折线距离阈值拟合(linear approxi mation distance threshol-ding,LADT)变换相结合的压缩算法,并结合DICOM标准定义了压缩波形的私有传输语法,通过调用波形写入模块将压缩数据存储为DICOM格式文件。经过实验和调试,在本EECP实验室中成功实现了EECP采集数据的压缩、解压以及在EECP工作站之间的正确传输和显示。     

PACS中DICOM图像传输与存取系统的设计

为实现DICOM图像的传输和存取,本研究通过分析DICOM通信机制和DICOM图像的特性,设计了DICOM图像传输与存取系统。该系统用多线程实现DICOM图像传输,数据库采用SQL2005。实验结果表明,该系统能基本实现传输和存取的功能,有助于实现微型PACS。     

基于Windows平台的DICOM医学影像显示技术研究

DICOM3．0是PACS、HIS系统和远程医疗技术实现的关键所在，它规范了医学图像及各种数字信息在异构系统和设备之间存储、传送时的文件格式和语义描述。通过对标准DICOM3．0医学图像格式的分析，以Windows2000为平台，深入讨论了标准CT和MR医学图像在通用微机上的开窗显示技术，并在DICOM标准原有算法的基础上提出了一种改进的图像显示算法。     

医学图像存档和传输系统打印管理服务功能的实现

打印管理是组成医学图像存档和传输(PACS)系统的重要功能模块，必须按照DICOM标准来设计。本简述DICOM中的传输和打印管理服务的基本内容，对打印管理模块的功能进行了分析，在此基础上介绍了打印管理模块的实现，并列出了用DELPHI实现的程序模块以及实现时需注意的一些具体问题。     

医学图像存档和传输系统打印管理服务功能的实现

打印管理是组成医学图像存档和传输(PACS)系统的重要功能模块，必须按照DICOM标准来设计。本简述DICOM中的传输和打印管理服务的基本内容，对打印管理模块的功能进行了分析，在此基础上介绍了打印管理模块的实现，并列出了用DELPHI实现的程序模块以及实现时需注意的一些具体问题。     

Quality of Compressed Medical Images

Previous studies have shown that Joint Photographic Experts Group (JPEG) 2000 compression is better than JPEG at higher compression ratio levels. However, some findings revealed that this is not valid at lower levels. In this study, the qualities of compressed medical images in these ratio areas (∼20), including computed radiography, computed tomography head and body, mammographic, and magnetic resonance T1 and T2 images, were estimated using both a pixel-based (peak signal to noise ratio) and two 8 × 8 window-based [Q index and Moran peak ratio (MPR)] metrics. To diminish the effects of blocking artifacts from JPEG, jump windows were used in both window-based metrics. Comparing the image quality indices between jump and sliding windows, the results showed that blocking artifacts were produced from JPEG compression, even at low compression ratios. However, even after the blocking artifacts were omitted in JPEG compressed images, JPEG2000 outperformed JPEG at low compression levels. We found in this study that the image contrast and the average gray level play important roles in image compression and quality evaluation. There were drawbacks in all metrics that we used. In the future, the image gray level and contrast effect should be considered in developing new objective metrics.     

Linking Whole-Slide Microscope Images with DICOM by Using JPEG2000 Interactive Protocol

The use of digitized histopathologic specimens (also known as whole-slide images (WSIs)) in clinical medicine requires compatibility with the Digital Imaging and Communications in Medicine (DICOM) standard. Unfortunately, WSIs usually exceed DICOM image object size limit, making it impossible to store and exchange them in a straightforward way. Moreover, transmitting the entire DICOM image for viewing is ineffective for WSIs. With the JPEG2000 Interactive Protocol (JPIP), WSIs can be linked with DICOM by transmitting image data over an auxiliary connection, apart from patient data. In this study, we explored the feasibility of using JPIP to link JPEG2000 WSIs with a DICOM-based Picture Archiving and Communications System (PACS). We first modified an open-source DICOM library by adding support for JPIP as described in the existing DICOM Supplement 106. Second, the modified library was used as a basis for a software package (JVSdicom), which provides a proof-of-concept for a DICOM client–server system that can transmit patient data, conventional DICOM imagery (e.g., radiological), and JPIP-linked JPEG2000 WSIs. The software package consists of a compression application (JVSdicom Compressor) for producing DICOM-compatible JPEG2000 WSIs, a DICOM PACS server application (JVSdicom Server), and a DICOM PACS client application (JVSdicom Workstation). JVSdicom is available for free from our Web site (), which also features a public JVSdicom Server, containing example X-ray images and histopathology WSIs of breast cancer cases. The software developed indicates that JPEG2000 and JPIP provide a well-working solution for linking WSIs with DICOM, requiring only minor modifications to current DICOM standard specification.     

基于离散小波变换的JPEG 2000标准对肺部CT图像的无损压缩

探索基于小波变换对肺部CT图像进行无损雎缩的新方法.采用基于离散小波变换方法的JPEG2000标准对3019张肺部CT图像进行无损压缩,并针对压缩后图像效果进行统计分析.结果表明,该方法不但可以达到12.0的高压缩比,而且具有较高的图像尤损压缩质量,为临床CT医学影像的储存与诊断,提供了有益的技术与方法.     

JPEG2000 Still Image Coding Quality

This work demonstrates the image qualities between two popular JPEG2000 programs. Two medical image compression algorithms are both coded using JPEG2000, but they are different regarding the interface, convenience, speed of computation, and their characteristic options influenced by the encoder, quantization, tiling, etc. The differences in image quality and compression ratio are also affected by the modality and compression algorithm implementation. Do they provide the same quality? The qualities of compressed medical images from two image compression programs named Apollo and JJ2000 were evaluated extensively using objective metrics. These algorithms were applied to three medical image modalities at various compression ratios ranging from 10:1 to 100:1. Following that, the quality of the reconstructed images was evaluated using five objective metrics. The Spearman rank correlation coefficients were measured under every metric in the two programs. We found that JJ2000 and Apollo exhibited indistinguishable image quality for all images evaluated using the above five metrics (r > 0.98, p < 0.001). It can be concluded that the image quality of the JJ2000 and Apollo algorithms is statistically equivalent for medical image compression.     

Clinical Evaluation of Compression Ratios using JPEG2000 on Computed Radiography Chest Images

The efficient compression of radiographic images is of importance for improved storage and network utilization in support of picture archiving and communication systems (PACS) applications. The DICOM Working Group 4 adopted JPEG2000 as an additional compression standard in Supplement 61 over the existing JPEG. The wavelet-based JPEG2000 can achieve higher compression ratios with less distortion than the Discrete Cosine Transform (DCT)-based JPEG algorithm. However, the degradation of JPEG2000-compressed computed radiography (CR) chest images has not been tested comprehensively clinically. The authors evaluated the diagnostic quality of JPEG2000-compressed CR chest images with compression ratios from 5:1 to 200:1. An ROC (receiver operating characteristic analysis) and t test were performed to ascertain clinical performance using the JPEG2000-compressed images. The authors found that compression ratios as high as 20:1 can be utilized without affecting lesion detectability. Significant differences between the original and the compressed CR images were not recognized up to compression ratio of 50:1 within a confidence level of 99%.     

A comparison of wavelet and Joint Photographic Experts Group lossy compression methods applied to medical images

This presentation focuses on the quantitative comparison of three lossy compression methods applied to a variety of 12-bit medical images. One Joint Photographic Exports Group (JPEG) and two wavelet algorithms were used on a population of 60 images. The medical images were obtained in Digital Imaging and Communications in Medicine (DICOM) file format and ranged in matrix size from 256 × 256 (magnetic resonance [MR]) to 2,560 × 2,048 (computed radiography [CR], digital radiography [DR], etc). The algorithms were applied to each image at multiple levels of compression such that comparable compressed file sizes were obtained at each level. Each compressed image was then decompressed and quantitative analysis was performed to compare each compressed-thendecompressed image with its corresponding original image. The statistical measures computed were sum of absolute differences, sum of squared differences, and peak signal-to-noise ratio (PSNR). Our results verify other research studies which show that wavelet compression yields better compression quality at constant compressed file sizes compared with JPEG. The DICOM standard does not yet include wavelet as a recognized lossy compression standard. For implementers and users to adopt wavelet technology as part of their image management and communication installations, there has to be significant differences in quality and compressibility compared with JPEG to justify expensive software licenses and the introduction of proprietary elements in the standard. Our study shows that different wavelet implementations vary in their capacity to differentiate themselves from the old, established lossy JPEG.     

联合图像专家组2000图像压缩方法的核医学应用研究

为研究联合图像专家组2000(Jo in t Photograph ic Expert G roup 2000,JPEG 2000)图像压缩方法在核医学中的应用,将无病变和有病变核医学静态图像用JPEG 2000软件压缩。对无损压缩图像,测量其压缩比。对有损压缩图像,由医生阅片,根据其结论作接收器操作特性(R ece iver operating characteristic,ROC)分析,获得各种图像压缩比的ROC曲线下的面积(A rea under curve,AUC),以其大小评价图像诊断质量;并将原始图像组AUC与各有损压缩图像组的AUC作配对t检验。实验发现,无损压缩的图像压缩比为(1.34±0.05)∶1。而有损压缩比越大,AUC越小。原始图像与压缩图像比较,压缩比为10∶1时没有显著性差异,压缩比更大时则有显著性差异。实验结果表明,无损压缩方法压缩比低,实用意义不大。有损压缩比不大于10∶1时,核医学静态图像的诊断质量得以保留。对核医学中的其它图像形式,可根据的图像性质,特别是固有统计噪声的大小,适当增减压缩比。     

基于DICOM的医学影像设备接口设计与实现

医学影像存档与通讯系统(Picture Archiving and Communication Systems,PACS)是目前医院信息化建设的热点,医学数字成像和通信标准(Digital Imaging and Communication in Medicine,DICOM)是有关医学图像及其相关信息的数据编码及通讯的国际标准,支持DICOM标准是医学影像设备并入PACS网络的必要条件。为使目前尚不符合DICOM标准的影像设备有效并入PACS系统,必须为其添加DICOM接口。我们介绍了DICOM信息模型并实现了接口的软件系统,重点介绍了应用VisualC 编程实现DICOM服务中的C-STORE和DCM文件的读写功能。     

The impact of image information on compressibility and degradation in medical image compression

The aim of the study was to demonstrate and critically discuss the influence of image information on compressibility and image degradation. The influence of image information on image compression was demonstrated on the axial computed tomography images of a head. The standard Joint Photographic Expert Group (JPEG) and JPEG 2000 compression methods were used in compression ratio (CR) and in quality factor (QF) compression modes. Image information was estimated by calculating image entropy, while the effects of image compression were evaluated quantitatively, by file size reduction and by local and global mean square error (MSE), and qualitatively, by visual perception of distortion in high and low contrast test patterns. In QF compression mode, a strong correlation between image entropy and file size was found for JPEG (r=0.87, p < 0.001) and JPEG 2000 (r=0.84, p < 0.001), while corresponding local MSE was constant (4.54) or nearly constant (2.36-2.37), respectively. For JPEG 2000 CR compression mode, CR was nearly constant (1:25), while local MSE varied considerably (2.26 and 10.09). The obtained qualitative and quantitative results clearly demonstrate that image degradation highly depends on image information, which indicates that the degree of image degradation cannot be guaranteed in CR but only in QF compression mode. CR is therefore not a measure of choice for expressing the degree of image degradation in medical image compression. Moreover, even when using QF compression modes, objective evaluation, and comparison of the compression methods within and between studies is often not possible due to the lack of standardization of compression quality scales.     

Adaptive threshold-based block classification in medical image compression for teleradiology

Telemedicine, among other things, involves storage and transmission of medical images, popularly known as teleradiology. Due to constraints on bandwidth and storage capacity, a medical image may be needed to be compressed before transmission/storage. Among various compression techniques, transform-based techniques that convert an image in spatial domain into the data in spectral domain are very effective. Discrete cosine transform (DCT) is possibly the most popular transform used in compression of images in standards like Joint Photographic Experts Group (JPEG). In DCT-based compression the image is split into smaller blocks for computational simplicity. The blocks are classified on the basis of information content to maximize compression ratio without sacrificing diagnostic information. The present paper presents a technique along with computational algorithm for classification of blocks on the basis of an adaptive threshold value of variance. The adaptive approach makes the classification technique applicable across the board to all medical images. Its efficacy is demonstrated by applying it to CT, X-ray and ultrasound images and by comparing the results against the JPEG in terms of various objective quality indices.