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Multiresolution Lossy-to-Lossless Coding of MRI Objects

  • Habibollah Danyali
  • Alfred Mertins
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)

Abstract

This paper proposes an object-based, highly scalable, lossy-to-lossless coding approach for magnetic resonance (MR) images. The proposed approach, called OBHS-SPIHT, is based on the well known set partitioning in hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. It progressively encodes each slice of the MR data set separately in a multiresolution fashion from low resolution to full resolution and in each resolution from low quality to lossless quality. To achieve more compression efficiency, the algorithm only encodes the main object of interest in the input data set, and ignores the unnecessary background. The experimental results show the efficiency of the proposed algorithm for multiresolution lossy-to-lossless MRI data coding. OBHS-SPIHT, is a very attractive coding approach for medical image information archiving and transmission applications especially over heterogeneous networks.

Keywords

Lossless Compression Object Code Magnetic Resonance Data Lossless Code Shape Mask 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Habibollah Danyali
    • 1
  • Alfred Mertins
    • 2
  1. 1.Department of Electrical EngineeringUniversity of KurdistanSanandajIran
  2. 2.Signal Processing Group, Institute of PhysicsUniversity of OldenburgOldenburgGermany

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