Compression and accelerated rendering of volume data using DWT

Two-dimensional (2-D) images cannot convey information on object depth and location relative to the surfaces. The medical community is increasingly using three-dimensional (3-D) visualization techniques to view data from CT scans, MRI etc. 3-D images provide more information on depth and location in the spatial domain to help surgeons making better diagnoses of the problem. 3-D images can be constructed from 2-D images using 3-D scalar algorithms. With recent advances in communication techniques, it is possible for doctors to diagnose and plan treatment of a patient who lives at a remote location. It is made possible by transmitting relevant data of the patient via telephone lines. If this information is to be reconstructed in 3-D, then 2-D images must be transmitted. However 2-D dataset storage occupies a lot of memory. In addition, visualization algorithms are slow. We describe in this paper a scheme which reduces the data transfer time by only transmitting information that the doctor wants. Compression is achieved by reducing the amount of data transfer. This is possible by using the 3-D wavelet transform applied to 3-D datasets. Since the wavelet transform is localized in frequency and spatial domain, we transmit detail only in the region where the doctor needs it. Since only ROI (Region of Interest) is reconstructed in detail, we need to render only ROI in detail, thus we can reduce the rendering time.