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Semi-supervised Cluster Analysis of Imaging Data

In this paper, we present a semi-supervised clustering-based framework for discovering coherent subpopulations in heterogeneous image sets. Our approach involves limited supervision in the form of labeled instances from two distributions that reflect a rough guess about subspace of features that are...

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Detalles Bibliográficos
Main Authors: Filipovych, Roman, Resnick, Susan M., Davatzikos, Christos
Formato: Artigo
Idioma:Inglês
Publicado: 2010
Assuntos:
Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC3008313/
https://ncbi.nlm.nih.gov/pubmed/20933091
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2010.09.074
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