3D volume segmentation aims at partitioning the voxels into 3D objects (sub-volumes) which represent meaningful physical entities. Multi-resolution analysis (MRA) allows for the preservation of an image according to certain levels of resolution or blurring. The quality of this approach makes it useful in image compression, de-noising, and classification or segmentation. This paper focuses on the implementation of a medical volume segmentation technique using 3D Discrete Wavelet Transform (3D-DWT). Principle Component Analysis (PCA) has been presented to reduce the dimensionality of the 3D volume as a pre-processing step of 3D-DWT to accelerate the segmentation process.
["Shadi Al Zu'bi", 'Naveed Islam', 'Maysam F. Abbod']
3D Multiresolution Analysis for reduced features segmentation of medical volumes using PCA