Arif Arif Sameh, Mansor Sarina, Logeswaran Rajasvaran, Karim Hezerul Abdul
Faculty of Engineering, Multimedia University, 63100, Cyberjaya, Selangor, Malaysia.
J Med Syst. 2015 Feb;39(2):5. doi: 10.1007/s10916-015-0200-z. Epub 2015 Jan 28.
The massive number of medical images produced by fluoroscopic and other conventional diagnostic imaging devices demand a considerable amount of space for data storage. This paper proposes an effective method for lossless compression of fluoroscopic images. The main contribution in this paper is the extraction of the regions of interest (ROI) in fluoroscopic images using appropriate shapes. The extracted ROI is then effectively compressed using customized correlation and the combination of Run Length and Huffman coding, to increase compression ratio. The experimental results achieved show that the proposed method is able to improve the compression ratio by 400 % as compared to that of traditional methods.
荧光透视及其他传统诊断成像设备产生的海量医学图像需要大量数据存储空间。本文提出了一种有效的荧光透视图像无损压缩方法。本文的主要贡献在于使用合适的形状提取荧光透视图像中的感兴趣区域（ROI）。然后，利用定制的相关性以及行程编码和哈夫曼编码的组合对提取的ROI进行有效压缩，以提高压缩率。实验结果表明，与传统方法相比，该方法能够将压缩率提高400%。
