Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
A study in interactive 3-D rotation using 2-D control devices
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
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Brain imaging methods used in experimental brain research such as Positron Emission Tomography (PET) and Functional Magnetic Resonance (fMRI) require the analysis of large amounts of data. Exploratory statistical methods can be used to generate new hypotheses and to provide a reliable measure of a given effect. Typically, researchers report their findings by listing those regions which show significant statistical activity in a group of subjects under some experimental condition or task. A number of methods create statistical parametric maps (SPMs) of the brain on a voxelbasis. In our approach statistics are computed not on individual voxels but on predefined anatomical regions-of-interest (ROIs). A correlation coefficient is used to quantify similarity in response for various regions during an experimental setting. Since the functional inter-relationships can become rather complex and spatially widespread, they are best understood in the context of the underlying 3-D brain anatomy. However, despite the power of the 3-D model, the relative location of ROIs in 3-D can be obscured due the inherent problem of presenting 3-D spatial information on a 2-D screen. In order to address this problem, we have explored a number of visualization techniques to aid the brain researcher in exploring the spatial relationships of brain activity. In this paper, we present a novel 3-D interface that allows the interactive exploration of correlation datasets.