“Visual navigation and classification of datasets in feature similarity space” by Bowman, Joshi and Van Horn
Conference:
Type:
Title:
- Visual navigation and classification of datasets in feature similarity space
Presenter(s)/Author(s):
Abstract:
Discovering and understanding relationship patterns within a feature-rich archive (e.g. quantifying the degree of neuroanatomical similarity between the scanned subjects of a Magnetic Resonance Imaging (MRI) repository) is a nontrivial task. Scientists and expert users employ a variety of commodity algorithms for automated statistical analysis of feature patterns within a collection. But such analysis assumes the user is an experienced statistician, and disregards human visual processing capability. In this work we define a visual process for exploring the structure, relationships and patterns within a neuroimaging archive. Through dataset placement, our three-dimensional environment expresses similarity among the data. The application facilitates further analysis via two-stage exploratory clustering and classification.
References:
1. Joshi, S., Bowman, I., and Van Horn, J. D. 2011 (In Press). Brain pattern analysis of corticle valued distributions. In Proceedings of the IEEE International Symposium on Biomedical Engineering, 1–4.
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