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MICCAI
2000
Springer
13 years 11 months ago
Small Sample Size Learning for Shape Analysis of Anatomical Structures
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...
BMCBI
2011
12 years 11 months ago
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray
CVPR
2007
IEEE
14 years 10 months ago
Optimal Dimensionality Discriminant Analysis and Its Application to Image Recognition
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
IPMI
2009
Springer
14 years 8 months ago
Fully-Automated White Matter Hyperintensity Detection With Anatomical Prior Knowledge and Without FLAIR
This paper presents a method for detection of cerebral white matter hyperintensities (WMH) based on run-time PD-, T1-, and T2weighted structural magnetic resonance (MR) images of t...
Charles DeCarli, Christopher Schwarz, Evan Fletche...
HPDC
2009
IEEE
14 years 2 months ago
Pluggable parallelisation
This paper presents the concept of pluggable parallelisation that allows scientists to develop “sequential like” codes that can take advantage of multi-core, cluster and grid ...
Rui C. Gonçalves, João Luís S...