title: Perceptually lossless medical image coding.
abstract: A novel perceptually lossless coder is presented for the compression of medical images. Built on the JPEG 2000 coding framework, the heart of the proposed coder is a visual pruning function, embedded with an advanced human vision model to identify and to remove visually insignificant/irrelevant information. The proposed coder offers the advantages of simplicity and modularity with bit-stream compliance. Current results have shown superior compression ratio gains over that of its information lossless counterparts without any visible distortion. In addition, a case study consisting of 31 medical experts has shown that no perceivable difference of statistical significance exists between the original images and the images compressed by the proposed coder.
authors.affiliation: School of Computer Science and Software Engineering, Monash University, VIC, Melbourne, Australia. dwu8@optusnet.com.au
authors.forename: David
authors.initials: D
authors.lastname: Wu
authors.forename: Damian M
authors.initials: DM
authors.lastname: Tan
authors.forename: Marilyn
authors.initials: M
authors.lastname: Baird
authors.forename: John
authors.initials: J
authors.lastname: DeCampo
authors.forename: Chris
authors.initials: C
authors.lastname: White
authors.forename: Hong Ren
authors.initials: HR
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D044962:Data Compression / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted