Wavelet-based lossless compression of coronary angiographic images

• Published in: IEEE transactions on medical imaging Vol. 18; no. 3; pp. 272 - 281
• Main Authors: Munteanu, A., Cornelis, J., Cristea, P.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.1999; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Angiography; Archiving; Biological and medical sciences; Biomedical imaging; Cardiovascular system; Coders; Coding; Computerized, statistical medical data processing and models in biomedicine; Coronary Angiography - methods; Coronary Disease - diagnostic imaging; General aspects. Methods; Humans; Image coding; Image compression; Image databases; Image Processing, Computer-Assisted - methods; Investigative techniques, diagnostic techniques (general aspects); Longitudinal waves; Lossless; Medical diagnostic imaging; Medical sciences; Partitioning; Partitioning algorithms; Picture archiving and communication systems; Quantization; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Teleradiology - methods; Wavelet coefficients; Wavelet transforms; Human; Radiodiagnosis; Angiography; Information system; Image processing; Coronary artery; Cardiovascular disease; Digital image; Information loss; Biomedical data processing; Telemedicine; Coding; Wavelet base; Database; Information compression; Biomedical engineering
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/42.764904

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).