Volumetric medical image compression using 3D listless embedded block partitioning

Area of Science:

• Medical Imaging
• Image Compression
• Signal Processing

Background:

• Medical image compression is crucial for efficient storage and transmission.
• Existing methods like 3D-SPIHT face limitations in compression efficiency and memory usage.
• Wavelet transforms and block coding are established techniques in image compression.

Purpose of the Study:

• To introduce a novel, listless variant of a 3D-block coding algorithm for enhanced medical image compression.
• To improve compression performance and reduce memory requirements compared to existing algorithms.
• To achieve rate and resolution scalability for medical imaging applications.

Main Methods:

• A 3D hybrid transform combining wavelet transform (spatial) and Karhunen-Loueve transform (spectral) was employed.
• Transformed coefficients were arranged in a 1D fashion, following wavelet coefficient distribution.
• A novel listless block coding algorithm (3D-HLCK) was applied to encode coefficients in an ordered-bit-plane fashion.

Main Results:

• The proposed 3D-HLCK algorithm demonstrated superior compression performance compared to 3D-SPIHT.
• 3D-HLCK showed competitive results against state-of-the-art 3D wavelet coders across various bit rates.
• Significant memory reduction was achieved due to the listless nature of the algorithm.
• Rate and resolution scalability comparable to 3D-SPIHT and 3D-SPECK were maintained.

Conclusions:

• 3D-HLCK offers a promising solution for efficient medical image compression.
• The algorithm provides a favorable trade-off between compression performance, memory usage, and scalability.
• This method is effective for compressing magnetic resonance, DICOM, and angiogram images.