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» Learning from Highly Structured Data by Decomposition
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ICIP
2006
IEEE
15 years 11 months ago
An Approach for Intersubject Analysis of 3D Brain Images Based on Conformal Geometry
Recent advances in imaging technologies, such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Diffusion Tensor Imaging (DTI) have accelerated brain res...
Guangyu Zou, Jing Hua, Xianfeng Gu, Otto Muzik
MICCAI
2009
Springer
15 years 11 months ago
Topological Correction of Brain Surface Meshes Using Spherical Harmonics
A brain surface reconstruction allows advanced analysis of structural and functional brain data that is not possible using volumetric data alone. However, the generation of a brain...
Rachel Aine Yotter, Robert Dahnke, Christian Gas...
BMCBI
2004
181views more  BMCBI 2004»
14 years 9 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
WAIM
2010
Springer
14 years 8 months ago
Mining Contrast Inequalities in Numeric Dataset
Finding relational expressions which exist frequently in one class of data while not in the other class of data is an interesting work. In this paper, a relational expression of th...
Lei Duan, Jie Zuo, Tianqing Zhang, Jing Peng, Jie ...
TVCG
2011
146views more  TVCG 2011»
14 years 4 months ago
Visibility Histograms and Visibility-Driven Transfer Functions
—Direct volume rendering is an important tool for visualizing complex data sets. However, in the process of generating 2D images from 3D data, information is lost in the form of ...
Carlos D. Correa, Kwan-Liu Ma