Robust analysis of MRS brain tumour data using t-GTM

Authors:
Alfredo Vellido;Paulo J. G. Lisboa;Dolores Vicente
Affiliations:
Universitat Politècnica de Catalunya (UPC), Soft Computing Group, C. Jordi Girona, 1-3, 08034, Barcelona, Spain;Liverpool John Moores University (LJMU), Neural Computation Group, Byrom St, L3 3AF, Liverpool, UK;Universitat Politècnica de Catalunya (UPC), Soft Computing Group, C. Jordi Girona, 1-3, 08034, Barcelona, Spain
Venue:
Neurocomputing
Year:
2006

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Abstract

This paper proposes a principled, self-organized, framework to manage two sources of uncertainty that are inherent in intelligent systems for medical decision support, namely outliers and missing data. The framework is applied to magnetic resonance spectra (MRS), which are indicators of the grade of malignancy in brain tumours. A model for multivariate data clustering and visualization, the generative topographic mapping (GTM), is re-formulated as a mixture of Student's t-distributions making it more robust to outliers while supporting the imputation of missing values. An important new development is the extension of the model to provide automatic feature relevance determination. Its effectiveness on the MRS data is demonstrated empirically.