Perceptually lossless coding of medical images - from abstraction to reality

Wu, D 2006, Perceptually lossless coding of medical images - from abstraction to reality, Doctor of Philosophy (PhD), Electrical and Computer Engineering, RMIT University.

Document type: Thesis
Collection: Theses

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Title Perceptually lossless coding of medical images - from abstraction to reality
Author(s) Wu, D
Year 2006
Abstract This work explores a novel vision model based coding approach to encode medical images at a perceptually lossless quality, within the framework of the JPEG 2000 coding engine. Perceptually lossless encoding offers the best of both worlds, delivering images free of visual distortions and at the same time providing significantly greater compression ratio gains over its information lossless counterparts. This is achieved through a visual pruning function, embedded with an advanced model of the human visual system to accurately identify and to efficiently remove visually irrelevant/insignificant information. In addition, it maintains bit-stream compliance with the JPEG 2000 coding framework and subsequently is compliant with the Digital Communications in Medicine standard (DICOM). Equally, the pruning function is applicable to other Discrete Wavelet Transform based image coders, e.g., The Set Partitioning in Hierarchical Trees. Further significant coding gains are exploited through an artificial edge segmentatio n algorithm and a novel arithmetic pruning algorithm. The coding effectiveness and qualitative consistency of the algorithm is evaluated through a double-blind subjective assessment with 31 medical experts, performed using a novel 2-staged forced choice assessment that was devised for medical experts, offering the benefits of greater robustness and accuracy in measuring subjective responses. The assessment showed that no differences of statistical significance were perceivable between the original images and the images encoded by the proposed coder.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Electrical and Computer Engineering
Keyword(s) Image compression
Medical imaging
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Created: Tue, 25 Jan 2011, 09:37:23 EST
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