实时动态数字减影血管造影系统

本文简要介绍最新研制的实时动态数字减影血管造影系统，该系统用普通微机及数字减影图象存储处理器实现实时动态数字减影。文中对系统硬件组成、电路结构、特别是对超大容量造影图象存储处理器、蒙片图象存储器及其电路逻辑框图作了较详细的论述，同时对系统的软件功能做一简要的介绍，最后给出左心室造影的减影图象     

数字减影血管造影术

数字减影血管造影术(Digital Subtraction,Anroggraphy简称DSA)是七十年代后期开始迅速发展的一种新的成象技术。它是计算技术、电视技术和影像增强技术相结合的产物。由于它的出现,克服了血管造影术的困难,使血管造影术大大前进了一步。 DSA可粗分为两类:时间型减影和能量型减影。时间型减影以时间作为参量,能有效地消除造影血管或器官上下复盖组织(包括软组织和骨骼)的影响,但对病人的运动很敏感。能量型减影以射线能量作为参数,可以抑制由于     

数字减影血管造影中双能量减影技术

双能量减影技术是在进行兴趣区(ROI)血管造影时.同时使用两种不同的管电压取得两帧图像,作为减影对进行减影.本文运用数学物理方法分析骨组织和软组织在高电压和低电压的减影特点,定量求出骨组织和软组织的厚度.双能量减影要求管电压在短时间内进行切换,难度较高,目前在临床上尚未普及.     

一种免疫荧光图像减影技术在鉴定drebrin E亚型的应用

目的:在缺乏drebrin E抗体的情况下利用一种新的免疫荧光计算机图像减影技术的方法鉴定drebrinE亚型。方法:应用drebrin非特异性抗体M2F6和drebrin A特异性抗体DAS2对成年大鼠脑冰冻切片进行双重免疫荧光染色,然后用计算机图像处理软件对同一切片的两种染色照片进行图像减影技术处理,观察drebrin E在成年大鼠脑中的分布情况。结果:通过免疫荧光计算机图像减影技术得到了drebrin E亚型的图像,确认了drebrin E在成年大鼠脑中吻侧迁移流、海马齿状回、梨状皮质的分布。结论:利用免疫荧光图像减影技术可以实现对drebrin E亚型的鉴定,为类似drebrin这样存在两种亚型的蛋白质鉴定提供了一种新的方法。     

LCV plus全数字减影血管造影机故障维修

通用电气(General Electric,GE)公司LCV plus全数字减影血管造影机是使用最先进的三轴系统设计的,并采用计算机控制的数字减影血管造影系统。具     

基于FPGA的实时数字血管减影系统

介绍了一种基于FPGA的实时数字血管减影系统.重点介绍了在数字血管减影过程中图像对数放大、减影、像素移位以及最大充盈等特殊要求的实现.该系统工作稳定,可靠地实现了X光图像1024×1024大小每秒30帧的实时减影处理,并可期望短期内应用于临床.     

时间减影在静脉肾盂造影中的应用价值研究

目的探讨数字X线机(DFR)时间减影对静脉肾盂造影的诊断价值,并与常规单纯DFR静脉肾盂造影比较.方法对38例运用数字(DFR)静脉肾盂造影的检查者,同时采用时间减影进行分析.检查结果正常16例,肾盂积水、肾结石、输尿管畸形、输尿管结石等22例.结论数字静脉肾盂造影检查+时间减影检查,较好地克服了传统造影方法的不足,为泌尿系统的诊断和治疗提供了更全面和确切的依据,取得了较好的临床效果.     

双重能量对比增强数字减影乳房造影术诊断乳腺癌可行

据Lewin JM [Radiology,2003,229(1):261-268]报道双重能量对比增强数字减影乳房造影术诊断乳腺癌可行。 Lewin JM 及其同事对26例乳房X 线片或临床病理证实的乳腺癌患者行双重能量对比增强数字减影乳房造影术。该技术按注射碘化对比造影剂的不同分高能量和低能量数字减影乳房X     

一种可变系数的对数脑血管减影算法研究

目的 针对数字减影血管造影（digital subtraction angiography,DSA）血管图像中非血管结构难以完全去除,严重干扰对血管分析与诊断的问题,本文寻求一种适用于脑血管DSA图像的减影方法.方法 根据X射线在人体组织中的吸收特性,提出一种可变系数的对数减影算法.该算法首先对造影前后的图像分别进行对数变换再相减,然后设计一个自适应的扩大系数,将对数减影后的图像进行灰度动态范围的扩大.结果 对源自临床的一个实际造影图像（蒙片和盈片）分别采用直接减影、一般的对数减影和本文的对数减影算法进行处理,三种方法中本文算法获得的图像非血管结构较少,对比度强.结论 实验结果证明,可变系数对数减影算法能有效消除或降低背景噪声,获得血管灰度一致、对比度较强的血管图像.     

数字减影血管造影中双能量减影技术

双能量减影技术是在进行兴趣区（ＲＯＩ）血管造影时。同时使用两种不同的管电压取得两帧图像,作为减影对进行减影。本文运用数学物理方法分析骨组织和软组织在高电压和低电压的减影特点,定量求出骨组织和软组织的厚度。双能量减影要求管电压在短时间内进行切换,难度较高,目前在临床上尚未普及。     

一种基于随机回归辨识理论的医学图像无损压缩方法

详细地介绍了一种基于随机回归识理论的医学图像无埚压缩方法，该方法的性能通过十幅Ｘ线胸部图像与ＤＰＣＭ方法进行了比较，实验结果表明：这种方法对实现医学图像的无损压缩是非常有效的。     

Three novel lossless image compression schemes for medical image archiving and telemedicine.

In this article, three novel lossless image compression schemes, hybrid predictive/vector quantization lossless image coding (HPVQ), shape-adaptive differential pulse code modulation (DPCM) (SADPCM), and shape-VQ-based hybrid ADPCM/DCT (ADPCMDCT) are introduced. All are based on the lossy coder, VQ. However, VQ is used in these new schemes as a tool to improve the decorrelation efficiency of those traditional lossless predictive coders such as DPCM, adaptive DPCM (ADPCM), and multiplicative autoregressive coding (MAR). A new kind of VQ, shape-VQ, is also introduced in this article. It provides predictive coders useful information regarding the shape characters of image block. These enhance the performance of predictive coders in the context of lossless coding. Simulation results of the proposed coders applied in lossless medical image compression are presented. Some leading lossless techniques such as DPCM, hierarchical interfold (HINT), CALIC, and the standard lossless JPEG are included in the tests. Promising results show that all these three methods are good candidates for lossless medical image compression.     

Displaying radiologic images on personal computers: Image storage and compression—Part 2

This is part 2 of our article on image storage and compression, the third article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Image compression is classified as lossless (nondestructive) or lossy (destructive). Common lossless compression algorithms include variable-length bit codes (Huffman codes and variants), dictionary-based compression (Lempel-Ziv variants), and arithmetic coding. Huffman codes and the Lempel-Ziv-Welch (LZW) algorithm are commonly used for image compression. All of these compression methods are enhanced if the image has been transformed into a differential image based on a differential pulse-code modulation (DPCM) algorithm. The LZW compression after the DPCM image transformation performed the best on our example images, and performed almost as well as the best of the three commercial compression programs tested. Lossy compression techniques are capable of much higher data compression, but reduced image quality and compression artifacts may be noticeable. Lossy compression is comprised of three steps: transformation, quantization, and coding. Two commonly used transformation methods are the discrete cosine transformation and discrete wavelet transformation. In both methods, most of the image information is contained in a relatively few of the transformation coefficients. The quantization step reduces many of the lower order coefficients to 0, which greatly improves the efficiency of the coding (compression) step. In fractal-based image compression, image patterns are stored as equations that can be reconstructed at different levels of resolution.     

基于滤波器组的ECG无损数据压缩技术

本文提出了一种基于整-整映射滤波组的数据无损压缩算法和优化编码方案。以MIT-BIH心律失常数据库为基础,通过多级整-整变换把心电信号（ECG）分解成在不同频带上的频率成分,然后对分解后的变换数据作统计分析,按空间优化和速度优化并重的原则,提出了一种适合ECG无损压缩的优化编码方法。用MIT-BIH（采样率为360Hz)数据库测试表明该算法的平均数据无损压缩率为2.52,平均解码次数为1.375,其中72%的数据仅需一次解码。这种数据无损压缩算法可用于开发更高性能的Holter系统。     

医学图像无损压缩与有损压缩技术的进展

本文对医学图像无损压缩和有损压缩的概念和应用进行了分析比较 ,并简要介绍了几种近年来发展的图像无损压缩方法 ,重点介绍了有损压缩中的小波图像压缩技术和分形图像压缩技术。在医学图像的压缩中 ,通过有效地结合无损压缩和有损压缩技术 ,可以在得到医学要求的图像保真度的前提上 ,达到较高的压缩比     

生物医学信号的近无损压缩

生物医学信号的压缩在临床中具有广泛的应用，但在实际应用中，医生们普遍认为有损压缩技术会使诊断信息丢失，只有无损压缩才能不失真地保留所有信息，因而临床诊断必须使用无损压缩。然而，事实并非如此，首先，在信号的采集和数字化的过程中就会引入量化误差和其他各种误差，即使用无损压缩，实际也是有损的；其次，无损压缩的压缩比很低，其压缩性能远不能与有损压缩相比，所以，在医学领域真正具有广泛应用需求的还是有损压缩技术，关键是如何控制好误差以确保信号的可信度。而一般的有损压缩技术，由于其对信号失真度缺乏严格的控制，因而不适合应用于医学领域，所以有必要研究特殊的有损压缩技术，这就是近无损压缩技术。为此，我们提出了一个能有效表征信号可信度的指标，在此基础上，结合生物医学信号非线性、非平稳性的特点，设计了一个基于上下文的生物医学信号近无损压缩算法，实验结果表明近无损压缩在保证信号可信度的前提下获得了比无损压缩更好的压缩结果。最后，我们还就近无损压缩技术的研究方向作了有益的探讨。     

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。     

Watermark Compression in Medical Image Watermarking Using Lempel-Ziv-Welch (LZW) Lossless Compression Technique

In teleradiology, image contents may be altered due to noisy communication channels and hacker manipulation. Medical image data is very sensitive and can not tolerate any illegal change. Illegally changed image-based analysis could result in wrong medical decision. Digital watermarking technique can be used to authenticate images and detect as well as recover illegal changes made to teleradiology images. Watermarking of medical images with heavy payload watermarks causes image perceptual degradation. The image perceptual degradation directly affects medical diagnosis. To maintain the image perceptual and diagnostic qualities standard during watermarking, the watermark should be lossless compressed. This paper focuses on watermarking of ultrasound medical images with Lempel-Ziv-Welch (LZW) lossless-compressed watermarks. The watermark lossless compression reduces watermark payload without data loss. In this research work, watermark is the combination of defined region of interest (ROI) and image watermarking secret key. The performance of the LZW compression technique was compared with other conventional compression methods based on compression ratio. LZW was found better and used for watermark lossless compression in ultrasound medical images watermarking. Tabulated results show the watermark bits reduction, image watermarking with effective tamper detection and lossless recovery.     

Lossless Compression of Volumetric Medical Images with Improved Three-Dimensional SPIHT Algorithm

This article presents a lossless compression of volumetric medical images with the improved three-dimensional (3-D) set partitioning in hierarchical tree (SPIHT) algorithm that searches on asymmetric trees. The tree structure links wavelet coefficients produced by 3-D reversible integer wavelet transforms. Experiments show that the lossless compression with the improved 3-D SPIHT gives improvement about 42% on average over two-dimensional techniques and is superior to those of prior results of 3-D techniques. In addition, we can easily apply different numbers of decomposition between the transaxial and axial dimensions, which is a desirable function when the coding unit of a group of slices is limited in size.     

基于整数小波变换和嵌入式编码的ECG信号压缩

针对一般的有损压缩方法不能同时实现无损压缩的情况,实现了一类基于整数小波变换和嵌入式编码的心电数据压缩方法,不仅能够进行有损压缩,也能够实现无损压缩.并且比较了EZW、SPIHT和SPECK三种主要的嵌入式编码算法的性能优劣,为移动心电监护以实时性、信号质量和编码可伸缩性为根据选择数据压缩方法提供了参考.