An Approach for Diagnostically Lossless Coding of Volumetric Medical Data Based on Wavelet and Just-Noticeable-Distortion Model

B. K. Chandrika, P. Aparna, S. Sumam David

Research output: Contribution to journalArticlepeer-review

Abstract

This paper explores a technique for visually/diagnostically lossless coding in the wavelet domain to effectively compress the three-dimensional medical image data. The quantisation module based on Just Noticeable Distortion (JND) for wavelets guarantees the visual quality in the reconstructed data. This method has been further extended to present the Volume of Interest (VOI) based technique that enables to preserve the quality of the diagnostically significant VOI region. The proposed method tested on several datasets outperforms the state-of-the-art methods. Apart from the conventional quality metric, Human Visual System (HVS) based quality metrics are also used to evaluate the visual quality of the reconstructed image. A subjective and objective evaluation carried out for VOI based coder shows that the quality-compression needs of the medical community are well addressed.

Original languageEnglish
JournalIETE Journal of Research
DOIs
Publication statusAccepted/In press - 2020

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science Applications
  • Electrical and Electronic Engineering

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