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Automatic quality control for wavelet-based compression of volumetric medical images using distortion-constrained
Shaou-Gang Miaou1, Shih-Tse Chen
1Multimedia Computing and Telecommunication Laboratory, Department of Electronic Engineering, Chung Yuan Christian University, 32023 Taiwan, R.O.C. miaou@wavelet.el.cycu.edu.tw
IEEE Transactions on Medical Imaging
|November 24, 2004
Summary
This study introduces a new wavelet-based compression method for volumetric medical images (VMI). The technique effectively preserves diagnostic features while significantly improving coding performance compared to existing methods.
Area of Science:
- Medical Imaging
- Signal Processing
- Data Compression
Background:
- Volumetric medical images (VMI) generate massive datasets, posing significant transmission and storage challenges.
- Lossy compression of VMI sequences necessitates preserving critical diagnostic features in reconstructed images.
Purpose of the Study:
- To develop an advanced lossy compression technique for VMI sequences that maintains diagnostic integrity.
- To introduce a distortion-constrained codebook replenishment (DCCR) mechanism for user-defined quality control.
Main Methods:
- A wavelet-based adaptive vector quantizer integrated with a DCCR mechanism.
- Combination of a novel codebook updating strategy with the Set Partitioning in Hierarchical Trees (SPIHT) technique.
- Development of an iterative fast searching algorithm utilizing an energy-quality curve for quality control.
Main Results:
- The proposed DCCR mechanism achieved superior coding gain and performance compared to pure SPIHT and JPEG2000.
- The iterative fast searching algorithm enabled quick, smooth, and reliable quality control.
- The method successfully maintained essential diagnostic features in compressed VMI sequences.
Conclusions:
- The developed wavelet-based compression technique offers an effective solution for VMI data challenges.
- The DCCR mechanism provides a robust method for achieving user-specified image quality in VMI compression.
- The proposed algorithm demonstrates significant advantages in coding performance and quality control for medical image compression.