Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms

• Published in: IEEE transactions on medical imaging Vol. 22; no. 3; pp. 459 - 470
• Main Authors: Zixiang Xiong, Xiaolin Wu, Cheng, S., Jianping Hua
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2003; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anatomy, Cross-Sectional - methods; Biomedical imaging; Context modeling; Databases, Factual; Decoding; Diagnostic Imaging - methods; Humans; Image coding; Imaging, Three-Dimensional - methods; Information Storage and Retrieval - methods; Magnetic Resonance Imaging - methods; Medical diagnostic imaging; Performance loss; Sample Size; Signal Processing, Computer-Assisted; Tomography, X-Ray Computed - methods; Transform coding; Video coding; Wavelet coefficients; Wavelet transforms
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2003.809585

We study lossy-to-lossless compression of medical volumetric data using three-dimensional (3-D) integer wavelet transforms. To achieve good lossy coding performance, it is important to have transforms that are unitary. In addition to the lifting approach, we first introduce a general 3-D integer wavelet packet transform structure that allows implicit bit shifting of wavelet coefficients to approximate a 3-D unitary transformation. We then focus on context modeling for efficient arithmetic coding of wavelet coefficients. Two state-of-the-art 3-D wavelet video coding techniques, namely, 3-D set partitioning in hierarchical trees (Kim et al., 2000) and 3-D embedded subband coding with optimal truncation (Xu et al., 2001), are modified and applied to compression of medical volumetric data, achieving the best performance published so far in the literature-both in terms of lossy and lossless compression.