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Compression assessment based on medical image quality concepts using computer-generated test images.

机译:基于医学图像质量概念的压缩评估,使用计算机生成的测试图像。

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摘要

Compression algorithms are widely used in medical imaging systems for efficient image storage, transmission, and display. In the acceptance of lossy compression algorithms in the clinical environment, important factors are the assessment of 'visually lossless' compression thresholds, as well as the development of assessment methods requiring fewer data and time than observer performance based studies. In this study a set of quantitative measurements related to medical image quality parameters is proposed for compression assessment. Measurements were carried out using region of interest (ROI) operations on computer-generated test images, with characteristics similar to radiographic images. As a paradigm, the assessment of the lossy Joint Photographic Expert Group (JPEG) algorithm, available in a telematics application for healthcare, is presented. A compression ratio of 15 was found as the visually lossless threshold for the JPEG lossy algorithm, in agreement with previous observer performance studies. Up to this ratio low contrast discrimination is not affected, image noise level is decreased, high contrast line-pair amplitude is decreased by less than 3%, and input/output gray level differences are minor (less than 1%). This type of assessment provides information regarding the type of loss, offering cost and time benefits, in parallel with the advantages of test image adaptation to the requirements of a certain imaging modality and clinical study.
机译:压缩算法广泛用于医学成像系统中,以进行有效的图像存储,传输和显示。在临床环境中接受有损压缩算法时,重要因素是对“视觉无损”压缩阈值的评估,以及评估方法的发展,其所需数据和时间少于基于观察者表现的研究。在这项研究中,提出了一组与医学图像质量参数有关的定量测量值,用于压缩评估。使用感兴趣区域(ROI)操作对计算机生成的测试图像进​​行测量,其特征类似于射线照相图像。作为范例,介绍了对有损医疗保健的远程信息处理应用程序中可用的有损联合图像专家组(JPEG)算法的评估。与先前的观察者性能研究一致,发现JPEG有损算法的视觉无损阈值为15的压缩比。达到该比率,不影响低对比度辨别力,降低图像噪声水平,将高对比度线对幅度降低小于3%,并且输入/输出灰度级差异很小(小于1%)。这种类型的评估可提供有关损失类型的信息,从而提供成本和时间收益,同时还可根据特定成像方式和临床研究的要求对测试图像进​​行调整。

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