DTI volume rendering techniques for visualising the brain anatomy

Abstract

Over the past few years Diffusion Tensor Imaging (DTI) has become an increasingly popular method for imaging the brain anatomy and diagnosing a variety of neurodegenerative diseases. Unfortunately the size and multi-dimensional nature of diffusion tensor data sets make it difficult to understand them. We use illuminated streamlines to compute high quality dense 3 visualisations of the 3 nerve fibre structure. Nerve fibres are extracted using a numerical integration technique and a fuzzy classifier which represents the probability that a sample point represents grey matter, white matter or Cerebral Spinal Fluid (CSF). We present two novel methods which improve the perception of the 3 arrangements of fibre tracts. The first method is a hardware accelerated algorithm which represents fibres as semi-transparent tubes with emphasised silhouettes. Because of the semi-transparent nature of the tubes inside structures are revealed. The enhancement of tube silhouettes improves the identification of individual fibre tracts and their 3 arrangement. The second method uses direct volume rendering and multiple colour and transparency look-up tables to represent the directional information of the nerve fibre structure and other tissue types simultaneously. The method can be used to represent finer details depending on the resolution of the noise texture employed depending on the choice of the opacity transfer functions fibre tracts can be represented semi-transparent or nearly opaque.