Implementing Direct Volume Visualisation with Spatial Classification
Mueller, Daniel C., Maeder, Anthony J., & O'Shea, Peter J. (2005) Implementing Direct Volume Visualisation with Spatial Classification. In APRS Workshop on Digital Image Computing (WDIC2005), 21/02/2005, Brisbane, Queensland.
Direct volume rendering (DVR) provides medical users with insight into datasets by creating a 3-D representation from a set of 2-D image slices (such as CT or MRI). This visualisation technique has been used to aid various medi-cal diagnostic and therapy planning tasks. Volume render-ing has recently become faster and more affordable with the advent of 3-D texture-mapping on commodity graphics hardware. Current implementations of the DVR algorithm on such hardware allow users to classify sample points (known as "voxels") using 2-D transfer functions (func-tions based on sample intensity and sample intensity gradi-ent magnitude). However, such 2-D transfer functions in-herently ignore spatial information. We present a novel modification to 3-D texture-based volume rendering allow-ing users to classify fuzzy-segmented, overlapping regions with independent 2-D transfer functions. This modification improves direct volume rendering by allowing for more sophisticated classification using spatial information.
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|Item Type:||Conference Paper|
|Keywords:||volume rendering, medical visualisaion, transfer functions|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > BIOMEDICAL ENGINEERING (090300) > Biomedical Engineering not elsewhere classified (090399)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
|Copyright Owner:||Copyright 2005 (please consult author)|
|Deposited On:||23 Jun 2005|
|Last Modified:||29 Feb 2012 23:12|
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