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Perceptually lossless medical image coding.

David Wu·Damian M Tan·Marilyn Baird·John DeCampo·Chris White·Hong Ren Wu
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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.

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AlgorithmsComputer GraphicsData CompressionImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-AssistedEvaluation StudyJournal Article

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David Wu, Damian M Tan, Marilyn Baird, John DeCampo, Chris White, Hong Ren Wu. 2006. Perceptually lossless medical image coding.. https://doi.org/10.1109/tmi.2006.870483

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