A Novel Medical Image Quality Index

A novel medical image quality index using grey relational coefficient calculation is proposed in this study. Three medical modalities, DR, CT and MRI, using 30 or 60 images with a total of 120 images used for experimentation. These images were first compressed at ten different compression ratios (10 ∼ 100) using a medical image compression algorithm named JJ2000. Following that, the quality of the reconstructed images was evaluated using the grey relational coefficient calculation. The results were shown consistent with popular objective quality metrics. The impact of different image aspects on four grey relational coefficient methods were further tested. The results showed that these grey relational coefficients have different slopes but very high consistency for various image areas. Nagai’s grey relational coefficient was chosen in this study because of higher calculation speed and sensitivity. A comparison was also made between this method and other windows-based objective metrics for various window sizes. Studies found that the grey relational coefficient results are less sensitive to window size changes. The performance of this index is better than some windows-based objective metrics and can be used as an image quality index.     

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.     

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。     

JPEG2000有损压缩对核医学图像的压缩效果的客观定量研究

从线源图像获得线源扩展函数、调制转移函数和峰-总计数比等参数,定量研究JPEG 2000有损压缩对核医学图像的压缩效果,并与实际分辨率图像和模拟分辨率图像的压缩效果进行对比。实验发现,随压缩比的增加,峰-总计数比曲线逐步下降,且噪声水平越高,曲线下降越快;但调制转移函数曲线和线源扩展函数曲线的半高宽无明显变化;随压缩比的增加,分辨率图像上可辨认出的条纹逐渐减少。实验结果表明,在压缩比和噪声水平变化时,峰-总计数比的变化与图像质量的变化规律一致,是用于图像压缩效果评价的较好的客观定量参数。     

Computed Tomography Image Compressibility and Limitations of Compression Ratio-Based Guidelines

Finding optimal compression levels for diagnostic imaging is not an easy task. Significant compressibility variations exist between modalities, but little is known about compressibility variations within modalities. Moreover, compressibility is affected by acquisition parameters. In this study, we evaluate the compressibility of thousands of computed tomography (CT) slices acquired with different slice thicknesses, exposures, reconstruction filters, slice collimations, and pitches. We demonstrate that exposure, slice thickness, and reconstruction filters have a significant impact on image compressibility due to an increased high frequency content and a lower acquisition signal-to-noise ratio. We also show that compression ratio is not a good fidelity measure. Therefore, guidelines based on compression ratio should ideally be replaced with other compression measures better correlated with image fidelity. Value-of-interest (VOI) transformations also affect the perception of quality. We have studied the effect of value-of-interest transformation and found significant masking of artifacts when window is widened.     

A Perceptual Evaluation of JPEG 2000 Image Compression for Digital Mammography: Contrast-Detail Characteristics

In this investigation the effect of JPEG 2000 compression on the contrast-detail (CD) characteristics of digital mammography images was studied using an alternative forced choice (AFC) technique. Images of a contrast-detail phantom, acquired using a clinical full-field digital mammography system, were compressed using a commercially available software product (JPEG 2000). Data compression was achieved at ratios of 1:1, 10:1, 20:1, and 30:1 and the images were reviewed by seven observers on a high-resolution display. Psychophysical detection characteristics were first computed by fitting perception data using a maximum-likelihood technique from which CD curves were derived at 50%, 62.5%, and 75% threshold levels. Statistical analysis indicated no significant difference in the perception of mean disk thickness up to 20:1 compression except for disk diameter of 1 mm. All other compression combinations exhibited significant degradation in CD characteristics.Certain aspects of this research were presented as a poster at the SCAR 2003 conference in Boston, MA, and was awarded the second place in the poster awards category by the SCAR committee.     

A Blurring Index for Medical Images

This study was undertaken to investigate a useful image blurring index. This work is based on our previously developed method, the Moran peak ratio. Medical images are often deteriorated by noise or blurring. Image processing techniques are used to eliminate these two factors. The denoising process may improve image visibility with a trade-off of edge blurring and may introduce undesirable effects in an image. These effects also exist in images reconstructed using the lossy image compression technique. Blurring and degradation in image quality increases with an increase in the lossy image compression ratio. Objective image quality metrics [e.g., normalized mean square error (NMSE)] currently do not provide spatial information about image blurring. In this article, the Moran peak ratio is proposed for quantitative measurement of blurring in medical images. We show that the quantity of image blurring is dependent upon the ratio between the processed peak of Moran's Z histogram and the original image. The peak ratio of Moran's Z histogram can be used to quantify the degree of image blurring. This method produces better results than the standard gray level distribution deviation. The proposed method can also be used to discern blurriness in an image using different image compression algorithms.     

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。     

一种分形方法在医学图像压缩中的应用

采用了一种新的基于分形的图像压缩方法对一脑CT图像进行了图像压缩。结果表明 :压缩比为 45 .0 2 ,峰值信噪比PSNR为 2 7.5db ,运算时间为 0 .75h。利用分形实现图像数据压缩处理可以获得高的压缩比 ,压缩后能够保持信号与图像特征基本不变 ,有较广的应用前景。     

Medical image compression using DCT-based subband decomposition and modified SPIHT data organization

OBJECTIVE: The work proposed a novel bit-rate-reduced approach for reducing the memory required to store a remote diagnosis and rapidly transmission it. METHOD: In the work, an 8x8 Discrete Cosine Transform (DCT) approach is adopted to perform subband decomposition. Modified set partitioning in hierarchical trees (SPIHT) is then employed to organize data and entropy coding. The translation function can store the detailed characteristics of an image. A simple transformation to obtain DCT spectrum data in a single frequency domain decomposes the original signal into various frequency domains that can further compressed by wavelet-based algorithm. In this scheme, insignificant DCT coefficients that correspond to a particular spatial location in the high-frequency subbands can be employed to reduce redundancy by applying a proposed combined function in association with the modified SPIHT. RESULTS AND CONCLUSIONS: Simulation results showed that the embedded DCT-CSPIHT image compression reduced the computational complexity to only a quarter of the wavelet-based subband decomposition, and improved the quality of the reconstructed medical image as given by both the peak signal-to-noise ratio (PSNR) and the perceptual results over JPEG2000 and the original SPIHT at the same bit rate. Additionally, since 8x8 fast DCT hardware implementation being commercially available, the proposed DCT-CSPIHT can perform well in high speed image coding and transmission.     

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.     

An Improved Medical Image Fusion Algorithm for Anatomical and Functional Medical Images

In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data, but, not an appropriate fusion algorithm for anatomical and functional medical images. In this paper, the traditional method of wavelet fusion is improved and a new fusion algorithm of anatomical and functional medical images,in which high-frequency and low-frequency coefficients are studied respectively. When choosing high-frequency coefficients, the global gradient of each subimage is calculated to realize adaptive fusion,so that the fused image can reserve the functional information;while choosing the low coefficients is based on the analysis of the neighborbood region energy, so that the fused image can reserve the anatomical image＇ s edge and texture feature. Experimental results and the quality evaluation parameters show that the improved fusion algorithm can enhance the edge and texture feature and retain the function information and anatomical information effectively.     

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.     

多模式医学图像的融合和配准技术

医学影像工程不断发展,出现了很多先进的成像设备,有力地支持了医学诊断和治疗。而以计算机技术为基础的成像后处理技术进一步提高了诊疗的可靠性。我们着重介绍了多模式医学图像融合和配准的技术内容和应用。     

一种医学图像几何特征的自动检测

医学图像配准的方法有许多种,它的原理都是选取合适的图像特征量,根据特征量再来确定配准变换,因此特征量的选取是图像配准的第一步。目前用于配准的图像特征量有多种,如图像边界、图像外标记点等。本文提供了一种提取图像脊特征,作为用于配准的特征量的方法,取得了良好效果。     

基于小波变换的医学图像压缩

简要介绍基于小波变换的图像压缩法，并提出了一种在matlab平台上实现基于小波的医学图像压缩的新方法。     

现代医学成像方法与图像压缩

现代医学成像设备的普遍应用，使数字医学图像在医学诊断领域所占的比重越来越大，它将逐渐取代传统的以胶片为基础的图像获取及存档方式。由于数字图像数据量大，存储时占内存容量多，传输时占信道容量大，所以对图像进行数据压缩以满足计算机联网和计算机多媒体技术发展的需要将成为必然。本文详细地介绍了各种数字图像的压缩方法及其特点，并在此基础上总结了当前的研究方向及未来的发展目标。     

计算机辅助诊断在医学影像学领域的研究进展

恶性肿瘤严重危害人类健康,早期诊断是治疗的关键。本文叙述了计算机辅助诊断在医学影像学领域中的研究进展。     

Using JPEG 2000 Interactive Protocol to Stream a Large Image or a Large Image Set

The electronic health record (EHR) is expected to improve the quality of care by enabling access to relevant information at the diagnostic decision moment. During deployment efforts for including images in the EHR, a main challenge has come up from the need to compare old images with current ones. When old images reside in a different system, they need to be imported for visualization which leads to a problem related to persistency management and information consistency. A solution consisting in avoiding image import is achievable with image streaming. In this paper we present, evaluate, and discuss two medical-specific streaming use cases: displaying a large image such as a digital mammography image and displaying a large set of relatively small images such as a large CT series.     

超声医学图像滤波算法研究进展

主要讨论超声医学图像滤波算法的研究现状,几种主要的滤波方法（多方位滤波方法、自适应权值调节滤波方法、自适应窗口选取滤波方法、两步法等）面临的问题及发展的方向。作者通过实践,将有关算法应用于超声医学图像的处理,给出了处理结果,进行了几种算法的比较分析。