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NIPS
2004
13 years 5 months ago
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...
Vladimir Koltchinskii, Manel Martínez-Ram&o...
CVPR
2005
IEEE
14 years 6 months ago
Machine Learning for Clinical Diagnosis from Functional Magnetic Resonance Imaging
Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active human brain. FMRI provides a sequence of 3D brain images with intensities representing ...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, No...
WSCG
2003
167views more  WSCG 2003»
13 years 5 months ago
Vector-valued Image Restoration with Applications to Magnetic Resonance Velocity Imaging
The analysis of blood flow patterns and the interaction between salient topological flow features and cardiovascular structure plays an important role in the study of cardiovascul...
Yin-Heung Pauline Ng, Guang-Zhong Yang
TMI
2010
206views more  TMI 2010»
12 years 11 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
MICCAI
2010
Springer
13 years 2 months ago
Detecting Brain Activation in fMRI Using Group Random Walker
Due to the complex noise structure of functional magnetic resonance imaging (fMRI) data, methods that rely on information within a single subject often results in unsatisfactory fu...
Bernard Ng, Ghassan Hamarneh, Rafeef Abugharbieh