Water phenomena are some of the most visually spectacular effects found in nature. This paper presents an efficient hybrid method to model turbulent water such as fast flowing rivers and waterfalls with the intent that the model can be used as part of a larger environment or scene. The model presented uses hydrostatic theory to incorporate a 2D height field and a particle system to model respectively the main volume and spray of turbulent water. The user is able to submit any environment formed from spheres and panels making the solution very flexible and adaptable.A smooth representation of the water surface is obtained by fitting a uniform B-Spline surface to the height field. Foam, spray and other turbulent effects are represented by particles which are rendered as spheres or billboards. Our results show that the model provides a nearly realistic simulation of turbulent water and for simple scenes nearly interactive speeds are possible which compares favorably with alternative techniques. For non-interactive applications ray tracing can be used to obtain higher quality results.
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 makes it difficult to understand them. We use illuminated streamlines to compute high quality dense 3D visualisations of the 3D 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 3D 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 3D 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.
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