3-D SPHIT Compression for MRI 3D Sequence Images

This paper presents a MATLAB-based 3-D SPHIT compression program along with valuable MRI 3D sequence images. The 3-D SPHIT (Set Partitioning in Hierarchical Trees) algorithm is an extended version of the popular wavelet-based compression method, specifically adapted for three-dimensional data processing. The MATLAB implementation features efficient tree structure organization for wavelet coefficients and progressive bitplane encoding, making it particularly suitable for compressing volumetric medical imaging data. The compressed version of this program runs efficiently in MATLAB environment, utilizing built-in functions for wavelet transformation (wavedec3) and implementing custom functions for spatial orientation tree management. Key algorithmic components include significance testing of coefficient sets, hierarchical tree traversal, and adaptive arithmetic coding for optimal compression ratios. Additionally, we provide high-quality MRI 3D sequence images that represent advanced medical imaging technology. These volumetric datasets are generated using magnetic resonance imaging techniques capable of producing detailed three-dimensional reconstructions for diagnostic and therapeutic applications. The images incorporate multiple sequence types including T1-weighted, T2-weighted, and FLAIR sequences, providing comprehensive anatomical and functional information crucial for medical research and clinical practice. These datasets serve as valuable resources for developing and testing medical image processing algorithms, with particular emphasis on compression, segmentation, and visualization techniques.