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» Image processing and data analysis: The multiscale approach
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TMI
2008
138views more  TMI 2008»
15 years 4 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
CVPR
2011
IEEE
15 years 24 days ago
Sparse Image Representation with Epitomes
Sparse coding, which is the decomposition of a vector using only a few basis elements, is widely used in machine learning and image processing. The basis set, also called dictiona...
Louise Benoit, Julien Mairal, Francis Bach, Jean P...
BMCBI
2004
208views more  BMCBI 2004»
15 years 4 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
149
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PAMI
2006
111views more  PAMI 2006»
15 years 4 months ago
Global Segmentation and Curvature Analysis of Volumetric Data Sets Using Trivariate B-Spline Functions
This paper presents a method to globally segment volumetric images into regions that contain convex or concave (elliptic) iso-surfaces, planar or cylindrical (parabolic) iso-surfa...
Octavian Soldea, Gershon Elber, Ehud Rivlin
SIGGRAPH
1996
ACM
15 years 8 months ago
Modeling and Rendering Architecture from Photographs: A Hybrid Geometry- and Image-Based Approach
We present a new approach for modeling and rendering existing architectural scenes from a sparse set of still photographs. Our modeling approach, which combines both geometry-base...
Paul E. Debevec, Camillo J. Taylor, Jitendra Malik