×
验证码:
换一张
忘记密码?
记住我
CORC
首页
科研机构
检索
知识图谱
申请加入
托管服务
登录
注册
在结果中检索
科研机构
长春光学精密机械与物... [2]
内容类型
会议论文 [2]
发表日期
2006 [2]
×
知识图谱
CORC
开始提交
已提交作品
待认领作品
已认领作品
未提交全文
收藏管理
QQ客服
官方微博
反馈留言
浏览/检索结果:
共2条,第1-2条
帮助
限定条件
发表日期:2006
内容类型:会议论文
专题:长春光学精密机械与物理研究所
第一署名单位
第一作者单位
通讯作者单位
已选(
0
)
清除
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
作者升序
作者降序
题名升序
题名降序
发表日期升序
发表日期降序
提交时间升序
提交时间降序
The compression and storage method of the same kind of medical images-DPCM (EI CONFERENCE)
会议论文
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
Zhao X.
;
Wei J.
;
Zhai L.
;
Liu H.
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2013/03/25
Medical imaging has started to take advantage of digital technology
opening the way for advanced medical imaging and teleradiology. Medical images
however
require large amounts of memory. At over 1 million bytes per image
a typical hospital needs a staggering amount of memory storage (over one trillion bytes per year)
and transmitting an image over a network (even the promised superhighway) could take minutes - too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. Several compression techniques with different compression ratio have been developed. However
the lossless techniques
which allow for perfect reconstruction of the original images
yield modest compression ratio
while the techniques that yield higher compression ratio are lossy
that is
the original image is reconstructed only approximately Medical imaging poses the great challenge of having compression algorithms that are lossless (for diagnostic and legal reasons) and yet have high compression ratio for reduced storage and transmission time. To meet this challenge
we are developing and studying some compression schemes
which are either strictly lossless or diagnostically lossless
taking advantage of the peculiarities of medical images and of the medical practice. In order to increase the Signal to-Noise Ratio (SNR) by exploitation of correlations within the source signal
a method of combining differential pulse code modulation (DPCM) is presented.
Lossless wavelet compression on medical image (EI CONFERENCE)
会议论文
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
Zhao X.
;
Wei J.
;
Zhai L.
;
Liu H.
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2013/03/25
An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image
thus facilitating accurate diagnosis
of course at the expense of higher bit rates
i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization
wavelet coding
neural networks
and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1
or even more)
they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image
but the achievable compression ratios are only of the order 2:1
up to 4:1. In our paper
we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time
we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance
so that all the low rate codes are included at the beginning of the bit stream. Typically
the encoding process stops when the target bit rate is met. Similarly
the decoder can interrupt the decoding process at any point in the bil stream
and still reconstruct the image. Therefore
a compression scheme generating an embedded code can start sending over the network the coarser version of the image first
and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.
©版权所有 ©2017 CSpace - Powered by
CSpace