医学图像存储与传输系统

PACS(picture archiving and cornmunications system)即图像存储与传输系统，是应用于现代化医院的各种数字医疗设备所产生的数字化医学图像信息的采集、存储、诊断、输出、管理、查询、信息处理的综合应用系统。目前，PACS系统在发达国家已经得到了广泛应用，我国的一些大型医院也初步建立起了PACS系统。     

PACS在放射科管理中的应用初探

目的：初步探讨PACS（picture archiving and communication system），医学影像存档与传输系统）在放射科质量管理中的价值。材料与方法：根据我院放射科设备情况及临床需求，建立一个基于DICOM3．0标准上的PACS系统，该系统由20个诊断工作站和30个图像浏览工作站组成。将非标准DICOM接口，及标准DICOM接口设备纳入DICOM服务器组成网，在该PACS网络中开展诊疗工作。结果：该PACS系统实现了放射科医学图像的获取、传输、存储、处理、输出、分析和诊断报告自动生成等功能，实现了放射科无胶片化管理。结论：PACS系统具有实用、经济、安全等特点，提高了工作效率和管理水平。在放射科管理方面具有广阔的应用前景。     

PACS海量数据中心

目的 本介绍了PACS数据中心的设计思想和关键技术，提出了解决PACS海量存储和“瓶颈效应”的一些方法。方法 PACS数据中心主要由PACS控制器、PACS管理服务器和PACS数据库服务器组成。PACS控制器负责响应PACS客户端的存储和查询／提取请求；PACS管理服务器负责对医学图像进行管理和归档；PACS数据库服务器负责对病人及其图像信息进行更新。在PACS数据中心内，各个服务器之间相互镜像，形成稳定的容错体系结构。PACS数据中心把各种存储设备融合成一个虚拟的海量存储池，图像分别以在线、近在线和离线等方式进行存储。在图像的传输上，PACS数据中心采用了自动路由和多通道并行等技术。结果 在上海华东医院两年多的临床运行中，PACS数据中心稳定可靠，无图像丢失，并且具有很高的查询提取速率。结论 PACS数据中心解决了医院内部海量数据的长期存储问题和PACS中常见的图像传输“瓶颈效应”问题。     

用提升格式CDF9/7小波变换和零树编码算法对X线医学图像压缩性能的研究

目的研究提升格式的CDF9/7小波变换和零树编码对X线医学图像的压缩性能.方法分别用基于提升格式CDF9/7小波变换的压缩方法和JPEG标准对X线医学图像进行压缩,包括乳腺钼靶图像、计算机摄影图像和计算机断层图像,压缩比从 3:1到40:1.用主观和客观方法评价压缩图像质量.结果与JPEG标准相比,本文的方法能够获得更好的图像质量和更高的压缩比;与基于Mallat算法的常规CDF9/7小波变换编码相比,提升格式的CDF9/7小波变换和零树编码可减少图像压缩的计算时间.结论本文提出的基于提升格式的CDF9/7小波变换和零树编码的医学图像压缩方法,可满足X线医学图像存储和传输的要求,并符合DICOM 3.0支持的最新的JPEG 2000图像压缩标准.     

浅谈PACS关键技术

PACS系统（picture archiving and communication systems）即医学图像归档与通讯系统，它是医院放射科或医院以及更大范围医院图像管理系统。各种各样的医学图像成像设备如CT、MRI、PET和UI等，产生了大量的影像数据，获取、存储、传输、显示和管理这些数据就是PACS系统的主要工作。     

基于整数小波变换和零树编码算法的医学图像压缩研究

现代医疗成象设备产生了大量高价值的医学图像,如何对信息的进行有效的存储、查询以及网络传输是一个亟待解决的问题.本文利用整数小波变换和零树编码算法对医学图像进行了压缩研究,试验表明,同传统JPEG标准相比,相同压缩比下本算法的峰值信噪比有明显的提高,同时本算法具有逐渐显现的特性,能够满足医学图像存储、查询以及网络传输的需求.     

医学图像查看系统Radworks的应用体会

目的：探讨医学图像查看系统Radworks的应用。材料与方法：通过Applicare公司开发的医学成像和PACS软件Radworks5．0系统获取、归档和传输放射科影像资料。结果：为了兼顾各种新旧不同的检查设备,部分图像的获取是通过有DICOM接口的新设备直接传输获取,而另一部分图像的获取是通过专用胶片扫描仪扫描X线照片获得,用光盘做数据的离线备份。结论：对于数据量不大、规模小的微型PACS,Radworks5．0尚可满足图像的获取、归档与传输等功能。     

数字X线胸片肺结节计算机辅助检测系统与PACS的整合应用

计算机图像存储和传输系统(picture archiving and communication system, PACS)在影像学科的医疗工作中具有重要作用.计算机辅助诊断(computer-aided diagnosis, CAD)技术是医学影像学发展的前沿技术[1-2].PACS系统和医用CAD系统的整合及应用未来将是医院影像科的发展方向.笔者就我院CAD系统在PACS中的整合及应用进行了初步观察,报道如下.     

基层医院放射科微型PACS的建立和维护

医学影像存档与传输系统(Picture Archiving and Communi-cating System,PACS),是建立在医学成像、图像处理、工作站及网络设计、数库、软件工程和通讯工程基础上的高技术产品,是近年来迅速发展起来的、旨在全面解决医学图像的获取、显示、存储、传送和管理的综合系统[1]。微型     

医院放射科DR及PACS系统的临床应用与管理

目的探讨医学图像存储与传输系统（PACS）与数字化X线摄影（DR）的临床应用与管理在医院发展中的作用。方法设备是改造升级后的岛津500mA直接数字平板X线摄影装置及医学影像工作站,由3位医生按三级医院的评片标准,对24987张使用DR及PACS系统后的影像照片质量进行评价,将照片影像质量分为甲、乙、丙、废片,并对其工作量及业务收支情况进行统计。结果选取数字化摄影检查的24987张照片中甲级片21520张（86．12％）,乙级片2320张（9．28％）,丙级片1115张（4．46％）,废片32张（0．13％）。与DR和PACS系统应用前相比较,DR和PACS系统应用后科室业务收入及检查人次大幅增加,耗材减少。结论PACS的建立使放射科的图像存储方便快捷,实现无胶片化储存,提高了诊断质量和工作效率。DR临床使用广泛,成像质量好,工作效率高,且辐射剂量少,放射科DR与PACS系统联合应用实现数字化后,在严格的质量控制和管理下,极大地提高了医院影像科的诊断水平和工作效率,同时提高了医院服务质量和管理水平,取得了良好的经济效益和社会效益。     

Data compression of X-ray cardio-angiographic image series

Medical x-ray images are increasingly stored and transmitted in a digital format. To reduce the required storage space and transmission bandwidth, data compression can be applied. In this paper we describe a new method for data compression of cardio-angiographie x-ray image series. The method is based on so-called overlappedtransform coding. A comparison with the well-known block-based transform-coding methods JPEG and MPEG is presented. We found that overlapped-transform coding does not introduce any blocking artefacts, in contrast to block-based transform coding, which introduces clearly visible blocking artefacts at compression ratios above 8. Clinical evaluations of the new method have pointed out that the image quality obtained at a compression ratio of 12 is adequate for diagnostic applications.     

Texture analysis in digitally-acquired echocardiographic images: the effect of JPEG compression and video storage

The analysis of texture in video-stored echocardiographic images is an established method to characterize myocardial pathologies. We investigated whether or not texture parameters calculated from video-stored images and those derived from the joint photographic expert group (JPEG) format compressed data are equivalent to those calculated from uncompressed digital images. Texture parameters were calculated using uncompressed digital data, images stored on videotape, and three forms of compressed digital data (baseline JPEG, JPEG 2000 and lossless JPEG 2000). Video storage heavily affected most texture parameters. Although first-order texture parameters derived from JPEG-compressed images were generally equivalent to those derived from the uncompressed data, several second-order parameters differed significantly. We conclude that texture of video-stored images is not comparable to that of digitally-stored images and that JPEG compression changes important second-order texture parameters. This observation should be taken into account when analyzing texture of modern image data (uncompressed or compressed) and comparing the results with earlier studies utilizing video-stored data.     

医学图像的零树小波编码

背景:医学数字图像必须是高质量的、高分辨率,所以数据量很大,如此巨大的数据量不利于图像存档与传输系统的运行和数字化医院、远程医疗的实现.因此,图像压缩成为图像存档与传输系统要解决的重要问题.目的:分析零树小波变编码算法原理并编程实现对医学数字图像的压缩,使之能够满足医学图像的传输和诊断要求.方法:应用嵌入式零树小波编码算法,探讨小波基和小波变换层数的选择,编程实现对医学数字图像的压缩.结果与结论:选择双正交小波基对医学图像进行4层小波变换实现压缩,获得了较高的峰值信噪比,取得了较好的压缩效果.     

小波变换医学DICOM图像压缩的研究

目的　利用小波变换实现对医学DICOM图像压缩。方法　分析小波变换技术特点及医学DICOM标准的数据结构 ,确定DICOM图像压缩的小波变换算法及编码方法。结果　用VC 实现基于小波技术的DICOM图像压缩。结论　该方法具备无损压缩、低比特速率有损压缩及渐进传输的优点 ,对我国远程医学和图像建档及通信系统的发展具有深远的意义     

Using JPEG image compression to facilitate telemedicine

Economical applications of teleradiology and telemedicine are limited to the existing telephone network infrastructure, which greatly limits the speed of digital information transfer. Telephone lines are inherently slow, requiring image transmission times to be unacceptably long for large, complex, or numerous images. JPEG (Joint Photographic Experts Group) image transmission has been shown to compress images to 10% of the original file size without a noticeable change in the quality of the image. This study was carried out to assess the quality of medical diagnostic images after JPEG compression and decompression. X-rays, computed tomography scans, and ultrasound samples were compressed and decompressed using JPEG. The compressed JPEG images were indistinguishable from the original images. The JPEG images were approximately 10% of the original file size. This would reduce image transmission times by 90% (eg, an unacceptable time of 50 minutes would be reduced to an acceptable time of 5 minutes). JPEG can be used to optimize teleradiology and telemedicine.     

Comparison of image compression viability for lossy and lossless JPEG and Wavelet data reduction in coronary angiography

Background: Lossless or lossy compression of coronary angiogram data can reduce the enormous amounts of data generated by coronary angiographic imaging. The recent International Study of Angiographic Data Compression (ISAC) assessed the clinical viability of lossy Joint Photographic Expert Group (JPEG) compression but was unable to resolve two related questions: (A) the performance of lossless modes of compression in coronary angiography and (B) the performance of newer lossy wavelet algorithms. This present study seeks to supply some of this information. Methods: The performance of several lossless image compression methods was measured in the same set of images as used in the ISAC study. For the assessment of the relative image quality of lossy JPEG and wavelet compression, the observers ranked the perceived image quality of computer-generated coronary angiograms compressed with wavelet compression relative to the same images with JPEG compression. This ranking allowed the matching of compression ratios for wavelet compression with the clinically viable compression ratios for the JPEG method as obtained in the ISAC study. Results: The best lossless compression scheme (LOCO-I) offered a mean compression ratio (CR) of 3.80:1. The quality of images compressed with the lossy wavelet-based method at CR = 10:1 and 20:1 was comparable to JPEG compression at CR = 6:1 and 10:1, respectively. Conclusion: The study has shown that lossless compression can exceed the CR of 2:1 usually quoted. For lossy compression, the range of clinically viable compression ratios can probably be extended by 50 to 100% when applying wavelet compression algorithms as compared to JPEG compression. These results can motivate a larger clinical study.     

Compression of EMG signals with wavelet transform and artificial neural networks

This paper presents a hybrid adaptive algorithm for the compression of surface electromyographic (S-EMG) signals recorded during isometric and/or isotonic contractions. This technique is useful for minimizing data storage and transmission requirements for applications where multiple channels with high bandwidth data are digitized, such as telemedicine applications. The compression algorithm proposed in this work uses a discrete wavelet transform for spectral decomposition and an intelligent dynamic bit allocation scheme implemented by an approach using the Kohonen layer, which improves the bit allocation for sections of the S-EMG with different characteristics. Finally, data and overhead information are packed by entropy coding. The results for the compression of isometric EMG signals showed that this algorithm has a better performance than standard wavelet compression algorithms presented in the literature (presenting a decrease of at least 5% in per cent residual difference (PRD) for the same compression ratio), and a performance that is comparable with the performance of algorithms based on an embedded zero-tree wavelet. For isotonic EMG signals, its performance is better than the performance of the algorithms based on embedded zero-tree wavelets (presenting a decrease in PRD of about 3.6% for the same compression ratios, in the useful compression range).     

Effect of lossy data compression on quantitative coronary measurements

With the accepted use of (lossy) data compression at low compression factors (2, 3 and 4 on the Philips DCI), the question was posed whether higher lossy compression ratios can also be used without statistically affecting the results of quantitative coronary arteriography. In this study the influence of two data compression schemes (LOT and JPEG) at three different compression factors (5, 8 and 12) on coronary measurements was assessed with the Automated Coronary Analysis (ACA) package. A series of 30 original acquired digital images were compressed and decompressed at the different factors, and together with the original non-compressed images processed using the ACA package. In these images a total of 37 obstructed coronary segments were analyzed twice to assess the intra-observer variabilities in the obstruction and reference diameters and in the percent diameter stenosis. The results of the first and second measurements in each image were averaged, and from the differences in corresponding images with different compression ratios, the inter-compression variability was obtained. The results show that the intra-observer systematic errors in the absolute diameters are all small (< 0.07 mm), and statistically not significantly different. The intra-observer random errors for the compressed/decompressed series, however, were all larger (up to 0.21 mm) than for the original series(< 0.13 mm). Statistically significant differences in the intra-observer random errors were found for the JPEG compression scheme at a compression ratio of 5 and for the LOT scheme at a compression ratio of 12. The inter-compression systematic errors in the absolute diameter measurements were also small (< 0.07 mm) and not significant, while the random errors were found to be high in the range between 0.23 mm and 0.31 mm. Given the higher intra-observer variabilities for the compressed/decompressed image series as compared to original images, and the fact that all inter- compression variabilities were found to be so high, we must conclude that the higher compression ratios affect the results of QCA in a negative sense. In conclusion, the use of lossy data compression with JPEG or LOT compression schemes at ratios 5, 8 and 12 must be discouraged for QCA.     

Networking of three dimensional sonography volume data.

Three-dimensioned (3D) sonography enables the examiner to store, instead of copies from single B-scan planes, a volume consisting of 300 scan planes. The volume is displayed on a monitor in form of three orthogonal planes--longitudinal, axial and coronal. Translation and rotation facilitates anatomical orientation and provides any arbitrary plane within the volume to generate organ optimized scan planes. Different algorithms allow the extraction of different information such as surface, or bone structures by maximum mode, or fluid filled structures, such as vessels by the minimum mode. The volume may contain as well color information of vessels. The digitized information is stored on a magnetic optical disc. This allows virtual scanning in absence of the patient under the same conditions as the volume was primarily stored. The volume size is dependent on different, examiner-controlled settings. A volume may need a storage capacity between 2 and 16 MB of 8-bit gray level information. As such huge data sets are unsuitable for network transfer, data compression is of paramount interest. 100 stored volumes were submitted to JPEG, MPEG, and biorthogonal wavelet compression. The original and compressed volumes were randomly shown on two monitors. In case of noticeable image degradation, information on the location of the original and compressed volume and the ratio of compression was read. Numerical values for proving compression fidelity as pixel error calculation and computation of square root error have been unsuitable for evaluating image degradation. The best results in recognizing image degradation were achieved by image experts. The experts disagreed on the ratio where image degradation became visible in only 4% of the volumes. Wavelet compression ratios of 20:1 or 30:1 could be performed without discernible information reduction. The effect of volume compression is reflected both in the reduction of transfer time and in storage capacity. Transmission time for a volume of 6 MB using a normal telephone with a data flow of 56 kB/s was reduced from 14 min to 28 s at a compression rate of 30:1. Compression reduced storage requirements from 6 MB uncompressed to 200 kB at a compression rate of 30:1. This successful compression opens new possibilities of intra- and extra-hospital and global information for 3D sonography. The key to this communication is not only volume compression, but also the fact that the 3D examination can be simulated on any PC by the developed 3D software. PACS teleradiology using digitized radiographs transmitted over standard telephone lines. Systems in combination with the management systems of HIS and RIS are available for archiving, retrieval of images and reports and for local and global communication. This form of tele-medicine will have an impact on cost reduction in hospitals, reduction of transport costs. On this fundament worldwide education and multi-center studies becomes possible.