title: Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms.
abstract: 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.
authors.affiliation: Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA. zx@ee.tamu.edu
authors.forename: Zixiang
authors.initials: Z
authors.lastname: Xiong
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Wu
authors.forename: Samuel
authors.initials: S
authors.lastname: Cheng
authors.forename: Jianping
authors.initials: J
authors.lastname: Hua
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods; D016208:Databases, Factual; D003952:Diagnostic Imaging / Q000379:methods; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D018401:Sample Size; D012815:Signal Processing, Computer-Assisted; D014057:Tomography, X-Ray Computed / Q000379:methods