Lossy Multiresolution Compression and Segmentation of 3D MR Images of the Head

In this paper, lossy compression of 3D MR images of the human brain is associated with a segmentation algorithm, in the context of an interactive brain sulci delineation application. Innuence of compression losses is analyzed according to the segmentation results. Lossy compression is performed by subband coding leading to a multiresolution representation of the image. Wavelets are adapted for medical images statistics. The decompressed images are segmented by Directional Watershed Transform (DWST), providing an accurate 3D segmentation of the brain. Impact of losses on the quality of the segmentation is estimated either by a 3D Chamfer distance function and by visual appreciation. In this article, we show that lossy compression can be combined with some applications, providing high compression ratio without signiicantly altering the results of the application.