Compression and accelerated rendering of volume data using discrete wavelet transform

Abstract

The medical community is increasingly using three-dimensional (3-D) visualization techniques to view data from CT scans, MRI etc. Two-dimensional (2-D) images cannot convey information on depth and location relative to the surfaces. Three-dimensional images provide more information on depth and location in the spatial domain to help surgeons making better diagnoses of the problem. Three-dimensional images are reconstructed from 2-D images using 3-D scalar algorithms. With 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, the problems associated in this setup would be (1) 2-D datasets are large and the transmitting time for these datasets is long; (2) rendering algorithms are slow, meaning that doctors can only view the 3-D image after a long delay. In this thesis, I shall describe 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 trans form 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 have modified existing rendering algorithms to reduce the rendering speed. Using these techniques it is shown that (1) 3-D data is compressed by transmitting detail in the portion where only the user wants it; (2) transmission time is reduced since data is compressed-(3) accelerated rendering is achieved since only ROI is rendered in detail.