医学图像无损压缩技术研究进展

医学成像技术已经成为现代临床医学诊断与治疗的核心支撑技术。然而,对于各种医学成像设备所获取的图像,庞大的数据量给图像存储与传输带来了巨大压力,并严重制约着医学图像的后续应用。随着医学成像设备分辨率的不断提高,所获取的图像数据量必将持续膨胀。因此,必须利用有效的压缩技术对其进行压缩。无损压缩能够完全保持原始医学图像的所有信息,在实际应用中获得了广泛的接受。本文对医学图像无损压缩技术的研究进展进行总结与分析,并对其发展趋势进行展望。     

有损压缩效应在胸部X 线照片的微细异常检测

远程放射会诊目前已成为公认的放射实践的组成部分。医学影像的庞大容量的解决方法是主要因素 ,影像容量问题只能是压缩图像 ,减少影像尺寸 ,无损压缩法在使用了图像内的信息量的同时减少了图像资料的容量从而可以完整的重建图像。这种无损技术明显的优点是完整的使用图像重建。但医学影像只能压缩到 2 :1～ 3:1。不可逆的或有损技术能按任何设计的比例压缩 ,但压缩比例越高 ,复制的图像与原始图像失真越大。这就促使我们去评价医学图像有损压缩的效果。由有损压缩产生的图像降级可以由数字计算进行测量。但是 ,以往所作的关于压缩对图像影…     

基于Visual C++和Matlab的磁共振影像增强后处理系统

目的:随着医学影像学的飞速发展,手术导航技术的应用及脑功能等图像分析研究的不断深入,基于医学数字成像和通信标准的医学影像分析与处理也随之成为医学图像处理领域中的热点。为便于科研人员研究相应的磁共振图像局部增强等后处理算法及进行图像分析,提出一种基于VisualC 和Matlab的磁共振影像增强后处理研发平台。方法:对北京协和医院放射科2005-01/10获取的部分磁共振医学数字成像和通信图像利用灰度扩展进行全局增强,利用基于数学形态学方法进行局部增强算法的研究。在程序实现上使用Matlab引擎实现VC 和Matlab混合编程处理医学数字成像和通信图像。结果:为磁共振图像进行增强局部对比度算法研究提供了一个研发平台,实现了位图图像与医学数字成像和通信图像的数据转换接口功能。结论:处理后的图像具有更好的应用价值,为图像局部对比度增强算法的研究提供一个有效的平台。在算法研制阶段采用VC和Matlab混合编程的方法可以提高算法研究效率。     

深度学习技术在细胞形态学图像处理中的研究进展

近年来,医学成像技术的飞速发展和普及应用使得医学图像分析进入了大数据时代,传统的利用医学成像设备进行筛查诊断的工作量巨大,并且由于患者的不断增多,往往伴随着患者病理学的个体差异、医生长时间辛苦的阅片工作和医生的主观评价等缺点,常会出现因假阳性率高而误诊的现象。深度学习技术在计算机视觉领域的巨大成功让医学图像实现计算机辅助筛查诊断成为可能。本文介绍了深度学习及其在细胞形态学图像处理领域的研究进展,总结了深度学习在细胞形态学图像分析中面临的挑战和可能的应对措施,并对应用前景进行了展望。     

深度学习技术在细胞形态学图像处理的研究进展

摘要：近年来，医学成像技术的飞速发展和普及应用使得医学图像分析进入了大数据时代，传统的利用医学成像设备进行筛查诊断的工作量巨大，并且由于患者的不断增多，往往伴随着患者病理学的个体差异、医生长时间辛苦的阅片工作和医生的主观评价等缺点，常会出现因假阳性率高而误诊的现象。深度学习技术在计算机视觉领域的巨大成功让医学图像实现计算机辅助筛查诊断成为可能。本文介绍了深度学习及其在细胞形态学图像处理领域的研究进展，总结了深度学习在细胞形态学图像分析中面临的挑战和可能的应对措施，并对应用前景进行了展望。     

基于Visual C＋＋和Matlab的磁共振影像增强后处理系统

目的：随着医学影像学的飞速发展，手术导航技术的应用及脑功能等图像分析研究的不断深入，基于医学数字成像和通信标准的医学影像分析与处理也随之成为医学图像处理领域中的热点.为便于科研人员研究相应的磁共振图像局部增强等后处理算法及进行图像分析，提出一种基于Visual C＋＋和Matlab的磁共振影像增强后处理研发平台. 方法：对北京协和医院放射科2005-01／10获取的部分磁共振医学数字成像和通信图像利用灰度扩展进行全局增强，利用基于数学形态学方法进行局部增强算法的研究：在程序实现上使用Matlab引擎实现VC＋＋和Matlab混合编程处理医学数字成像和通信图像. 结果：为磁共振图像进行增强局部对比度算法研究提供了一个研发平台，实现了位图图像与医学数字成像和通信图像的数据转换接口功能。 结论：处理后的图像具有更好的应用价值，为图像局部对比度增强算法的研究提供一个有效的平台：在算法研制阶段采用VC和Matlab混合编程的方法可以提高算法研究效率.     

基于小波变换的PET/CT图像融合算法研究进展

随着图像融合技术在影像学领域的不断发展,越来越多新的影像技术及成像设备出现。PET/CT将PET和CT两种模态的医学图像进行融合,优势互补,提高了医师诊断疾病的效率及准确率。小波变换在医学图像融合中有重要作用,基于小波变换的算法使融合后图像的细节更加清晰而易于诊断,已成为近年来医学图像融合领域中研究的重点。本文对基于小波变换的PET/CT图像融合算法的研究进展进行综述。     

医学超声成像中伪Chirp编码激励技术的仿真研究

与传统的脉冲回波成像技术相比，编码激励技术能够提高超声图像的信噪比。本首先对医学超声诊断系统中的发射声强进行了分析，得出了采用编码激励技术提高超声图像信噪比的上限。然后介绍了基于伪Chirp编码激励的超声成像系统，并进行了仿真。仿真试验表明伪Chirp激励能取得较好的效果。     

心脏成像中呼吸运动的抑制和补偿方法研究进展

成像技术已经在心血管疾病的诊断、治疗计划的制定和指导介入治疗等方面得到广泛应用。呼吸运动是指通过胸廓有节律地扩大和缩小来完成吸气和呼气,会引起心脏在三维空间中的整体平移,严重影响心脏图像的获取和图像质量。利用自由呼吸条件下采集的图像对呼吸运动进行建模,并对其进行抑制和补偿,成为解决这一问题的主要方法。本文在介绍呼吸运动对心脏成像影响的基础上,归纳呼吸运动抑制和补偿的方法,并着重介绍呼吸运动建模的方法。     

深度学习技术在医学影像中的应用

近十年来,人工智能(artificial intelligence,AI)在医学领域发展迅速,很大程度上得益于机器学习(machine learning,ML)技术的发展与进步,而机器学习也成为医学领域创新的新引擎。医学成像领域中,机器学习对图像重组、病变分割、计算机辅助检测(computer-aided detection,CADe)和诊断(computer-aided diagnosis,CADx)等方面的优化产生了积极影响[1,2]。与传统的医学图像分析技术相比,机器学习技术不需要由医学及技术领域专家为特定分析制定明确相关的功能。     

Image quality,compression and segmentation in medicine

This review considers image quality in the context of the evolving technology of image compression, and the effects image compression has on perceived quality. The concepts of lossless, perceptually lossless, and diagnostically lossless but lossy compression are described, as well as the possibility of segmented images, combining lossy compression with perceptually lossless regions of interest. The different requirements for diagnostic and training images are also discussed. The lack of established methods for image quality evaluation is highlighted and available methods discussed in the light of the information that may be inferred from them. Confounding variables are also identified. Areas requiring further research are illustrated, including differences in perceptual quality requirements for different image modalities, image regions, diagnostic subtleties, and tasks. It is argued that existing tools for measuring image quality need to be refined and new methods developed. The ultimate aim should be the development of standards for image quality evaluation which take into consideration both the task requirements of the images and the acceptability of the images to the users.     

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.     

The Kodak approach to digital cardiovascular imaging laboratories

Cine film had been a global standard in the cardiac catheterization lab for the acquisition, archive, review and exchange for decades. The advent of digital imaging in the cath lab heightened the desire to store cath procedure images in a digital format. The issues related to the development of a digital exchange standard, the data capacities and data rates, lossless and lossy compression, and techniques to obtain digital image data from the lab are discussed. In addition, Kodak's approach to cine film replacement with digital systems is described.     

Objective methods for optimizing JPEG compression of coronary angiographic images

Digital angiographic images contain a significant amount of redundancy as well as some irrelevant information and noise. Therefore, it is possible to reduce the number of bits required to represent an image considerably. The lossy JPEG standard may be used provided that no significant diagnostic information is lost. As implemented in presently available hard- and software in most cases the luminance quantization table (LQT) is applied for gray level images, which may only be scaled by a so-called quality factor. The questions arise whether it is possible and worthwhile to specify quantization tables for the particular characteristics of angiograms. To assess the quality performance quantitatively, global numerical quality measures and evaluations based on Hosaka-plots were performed. Those diagrams compare the errors introduced into areas of different local activity. By the newly introduced weighting of these errors with the relative occupancy of the respective classes of activity the results got more reproducible. The blocking and blurring effects introduced by lossy JPEG compression could be compared objectively. Two new quantization tables were derived from the transfer function of the angiographic X-ray system, the modulation transfer quantization table (MTQT) and the star pattern quantization table (SPQT). Both tables guarantee that the blurring of sharp edges is minimized so that no deterioration around a coronary lesion occurs. Based on the signal-to-noise ratio, the overall quality performance is the same as for theLQT. A general relation between the bit rate of the compressed image and the quality factor has been determined for images of high local activity and normally scaled coronary angiographic images (512 × 512).     

卷积神经网络探索孕中晚期胎儿大脑发育模式研究进展

MRI具有多参数、多序列,较高空间及组织分辨率等优势,已逐渐成为重要的产前影像学检查方法之一,可用于评估孕中晚期胎儿大脑发育;但受胎动等不可控因素影响,胎儿MR图像质量难以令人满意。卷积神经网络(CNN)是目前最常用于医学领域图像分割的深度学习算法,能够提升图像分辨率,已成功用于成人各系统,在胎儿领域尚处于起步阶段。本文就基于CNN探索孕中晚期胎儿大脑发育模式进展进行综述。     

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.     

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.