Naslov
Novel Prediction Based Technique for Efficient Compression of Medical Imaging Data

Autori
Knezović, Josip ; Kovač, Mario ; Žagar, Martin ; Mlinarić Hrvoje ; Hofman, Daniel

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Telemedicine Techniques and Applications

Urednik/ci
Georgi Graschew

Izdavač
IntechOpen

Grad
Rijeka

Godina
2011

Raspon stranica
169-184

ISBN
978-953-307-354-5

Ključne riječi
lossless image compression, predictive coding, blending predictors, contextual modeling

Sažetak
The annual volume of imaging data in modern paperless hospitals can approach up to 10 terabytes, heavily pressing the storage and transmission requirements. Utilizing efficient compression techniques for those data in order to reduce associated costs is very attractive from both viewpoints: financial and organizational. Although lossy techniques can yield better compression results, due to possible compression artifacts in the compressed image, they are less favored compared to lossless compression techniques in certain medical applications such as image-based diagnosis, archival etc. Moreover, new approaches in medical imaging such as 3D and 4D imaging and bio–modeling produce even greater amounts of image data. For efficient storage and transmission of those data and utilization of systems that exploit 3D and 4D imaging technologies, compression is inevitable. In this field, at least certain parts of images are required to be stored and transmitted without any loss of information. The lossless compression algorithm that we propose can also be efficiently employed for at least those vital parts of interest in this kind of applications. We propose a higly adaptive prediction-based lossless compression algorithm which models nontrivial image structures through selective blends of static predictors.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA