Title :
Wavelet-based lossless compression of coronary angiographic images
Author :
Munteanu, Adrian ; Cornelis, Jan ; Cristea, Paul
Author_Institution :
Dept. of Electron. & Inf. Processing, Vrije Univ., Brussels, Belgium
fDate :
3/1/1999 12:00:00 AM
Abstract :
The final diagnosis in coronary angiography has to be performed on a large set of original images. Therefore, lossless compression schemes play a key role in medical database management and telediagnosis applications. This paper proposes a wavelet-based compression scheme that is able to operate in the lossless mode. The quantization module implements a new way of coding of the wavelet coefficients that is more effective than the classical zerotree coding. The experimental results obtained on a set of 20 angiograms show that the algorithm outperforms the embedded zerotree coder, combined with the integer wavelet transform, by 0.38 bpp, the set partitioning coder by 0.21 bpp, and the lossless JPEG coder by 0.71 bpp. The scheme is a good candidate for radiological applications such as teleradiology and picture archiving and communications systems (PACS´s).
Keywords :
PACS; angiocardiography; data compression; image coding; medical image processing; telemedicine; visual databases; wavelet transforms; coronary angiographic images; embedded zerotree coder; integer wavelet transform; lossless JPEG coder; lossless mode; medical database management; medical diagnostic imaging; picture archiving & communications systems; set partitioning coder; telediagnosis applications; wavelet coefficients coding; wavelet-based lossless compression; Angiography; Biomedical imaging; Image coding; Image databases; Medical diagnostic imaging; Partitioning algorithms; Picture archiving and communication systems; Quantization; Wavelet coefficients; Wavelet transforms; Algorithms; Coronary Angiography; Coronary Disease; Humans; Image Processing, Computer-Assisted; Teleradiology;
Journal_Title :
Medical Imaging, IEEE Transactions on