Diagnostically Lossless Compression of X-Ray Angiographic Images through Background Suppression

Zhongwei Xu, Joan Bartrina-Rapesta, Victor Sanchez, J. Serra-Sagristà, Juan Munoz-Gomez
{"title":"Diagnostically Lossless Compression of X-Ray Angiographic Images through Background Suppression","authors":"Zhongwei Xu, Joan Bartrina-Rapesta, Victor Sanchez, J. Serra-Sagristà, Juan Munoz-Gomez","doi":"10.1109/DCC.2013.108","DOIUrl":null,"url":null,"abstract":"Summary form only given. X-ray angiographic (angio) images are widely used for identifying irregularities in the vascular system. Because of their high spatial resolution and the increasingly amount of X-ray angio images generated, compression of these images is becoming increasingly appealing. In this paper, we introduce a diagnostically lossless compression scheme for X-ray angio images. The coding scheme relies on a novel method based on ray casting and a-shapes for distinguishing the clinically relevant Region of Interest from the background. The background is then suppressed to increase data redundancy, allowing to achieve a higher coding performance. Experimental results suggest that the proposed scheme correctly identifies the Region of Interest in X-ray angio images and achieves more than 2 bits per pixel reduction in average as compared to the case of compression with no background suppression. Results are reported here for 20 out of 25 images compressed using various lossless compression methods.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"98 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2013.108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Summary form only given. X-ray angiographic (angio) images are widely used for identifying irregularities in the vascular system. Because of their high spatial resolution and the increasingly amount of X-ray angio images generated, compression of these images is becoming increasingly appealing. In this paper, we introduce a diagnostically lossless compression scheme for X-ray angio images. The coding scheme relies on a novel method based on ray casting and a-shapes for distinguishing the clinically relevant Region of Interest from the background. The background is then suppressed to increase data redundancy, allowing to achieve a higher coding performance. Experimental results suggest that the proposed scheme correctly identifies the Region of Interest in X-ray angio images and achieves more than 2 bits per pixel reduction in average as compared to the case of compression with no background suppression. Results are reported here for 20 out of 25 images compressed using various lossless compression methods.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过背景抑制对x射线血管造影图像进行诊断性无损压缩
只提供摘要形式。x线血管造影(angio)图像被广泛用于识别血管系统的不规则性。由于其高空间分辨率和生成的x射线血管图像的数量越来越多,这些图像的压缩变得越来越有吸引力。本文介绍了一种诊断性无损的x线血管图像压缩方案。该编码方案依赖于一种基于光线投射和a形的新方法来区分临床相关的感兴趣区域和背景。然后抑制后台以增加数据冗余,从而实现更高的编码性能。实验结果表明,与没有背景抑制的压缩相比,该方法能够正确地识别出x射线血管图像中的感兴趣区域,平均每像素降低2位以上。这里报告了使用各种无损压缩方法压缩25个图像中的20个图像的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Variable-to-Fixed-Length Encoding for Large Texts Using Re-Pair Algorithm with Shared Dictionaries Low Bit-Rate Subpixel-Based Color Image Compression Robust Adaptive Image Coding for Frame Memory Reduction in LCD Overdrive A Scalable Video Coding Extension of HEVC Low Complexity Embedded Quantization Scheme Compatible with Bitplane Image Coding
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1