Wavelet compression of nuclear medicine images
E Oczeretko1, W Rakowski, D Jurilewicz
1Institute of Computer Science, University of Białystok, Poland.
Nuclear Medicine Review. Central & Eastern Europe
|November 6, 2003
Summary
Wavelet transform image compression effectively reduces scintigram file sizes by 90:1, preserving image quality for practical medical applications.
Area of Science:
- Medical Imaging
- Signal Processing
- Data Compression
Background:
- Wavelet transform is an advanced mathematical technique for signal and image analysis.
- Wavelet-based methods are foundational to powerful lossy compression algorithms.
Purpose of the Study:
- To evaluate the effectiveness of wavelet transform for compressing static liver scintigrams.
- To assess the impact of compression on image quality and practical usability.
Main Methods:
- Static liver scans (128x128 matrix) were processed using a four-level wavelet transform.
- Biorthogonal filters with linear phase characteristics were employed for compression.
- The Set Partition in Hierarchical Trees (SPIHT) technique coded the wavelet coefficients.
Main Results:
- Achieved compression ratios of 90:1.
- Maintained high image quality with Peak Signal-to-Noise Ratio (PSNR) values greater than 32.
Conclusions:
- Wavelet compression offers significant disk space savings and reduced transmission times for scintigrams.
- Image decompression using this method does not substantially degrade diagnostic quality.
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