Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/122003
Title: IMPORTANCE-DRIVEN TRANSFER FUNCTION DESIGN FOR VOLUME VISUALIZATION OF MEDICAL IMAGES
Authors: CAI LILE
Keywords: Medical volume visualization, Transfer function design; Importance-driven methods; Visual attention
Issue Date: 18-Aug-2015
Citation: CAI LILE (2015-08-18). IMPORTANCE-DRIVEN TRANSFER FUNCTION DESIGN FOR VOLUME VISUALIZATION OF MEDICAL IMAGES. ScholarBank@NUS Repository.
Abstract: Transfer functions (TFs) play a key role in volume visualization. The non-intuitive nature of TF space combined with the extreme flexibility and lack of guidance and constraints makes the specification of the TF a highly challenging task in volume rendering. This motivates the extensive study of TF design. In this thesis, the TF design problem in volume visualization of medical images is investigated and several importance-driven TF design methods are proposed to better identify and highlight important structures in medical volumetric datasets. First, an automatic 2-D TF design method based on the matching of visibility distributions is introduced. In the second work, the TF domain is extended to higher dimensions in order to perform more sophisticated classification of volumetric objects, and a two-level clustering approach is proposed to address the higher-dimensional TF design problem. The third work moves away from manipulating TFs in the TF space and proposes a rule-enhanced TF design method that allows for a more effective separation of important structures in challenging datasets. Finally, an eye tracking experiment is conducted to study visual attention deployment in volume visualization. The proposed methods were tested on a variety of volumetric datasets. The results demonstrate the effectiveness and efficiency of the proposed methods.
URI: http://scholarbank.nus.edu.sg/handle/10635/122003
Appears in Collections:Ph.D Theses (Open)

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