基于感兴趣区域的医学图像压缩

Dalia Shaaban, M. Saad, A. Madian, H. Elmahdy
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引用次数: 2

摘要

医学图像显示出极大的兴趣,因为它需要在各种医学应用。为了减小传输速度较快的医学图像的尺寸;将感兴趣区域(ROI)和混合无损压缩技术应用于医学图像的压缩,在不丢失重要数据的情况下进行压缩。本文将根据图像的大小、峰值信噪比(PSNR)以及压缩和重建原始图像所需的时间,提出并评估一个拟议的模型。该模型的主要目标是最小化图像尺寸和传输时间。此外,提高PSNR是一个关键的挑战。实验结果表明,采用混合无损技术对医学图像进行ROI处理后,图像尺寸减小39%,压缩比和PSNR均有较好的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Compression Based on Region of Interest
Medical images show a great interest since it is needed in various medical applications. In order to decrease the size of medical images which are needed to be transmitted in a faster way; Region of Interest (ROI) and hybrid lossless compression techniques are applied on medical images to be compressed without losing important data. In this paper, a proposed model will be presented and assessed based on size of the image, the Peak Signal to Noise Ratio (PSNR),and the time that is required to compress and reconstruct the original image.The major objective of the proposed model is to minimize the size of image and the transmission time. Moreover, improving the PSNR is a critical challenge.The results of the proposed model illustrate that applying hybrid losslesstechniques on the ROI of medical images reduces size by 39% and gives better results in terms of the compression ratio and PSNR.
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