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» A Statistical Shape Model without Using Landmarks
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TMI
2002
248views more  TMI 2002»
13 years 8 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson
FBIT
2007
IEEE
14 years 24 days ago
Mapping Genetic Influences on Brain Shape Using Multi-Atlas Fluid Image Alignment
In this pilot study, we developed a set of computer vision based surface segmentation and statistical shape analysis algorithms to study genetic influences on brain structure in a...
Meena Mani, Yi-Yu Chou, Natasha Lepore, Agatha D. ...
CVPR
2009
IEEE
15 years 4 months ago
Learning Based Automatic Face Annotation for Arbitrary Poses and Expressions from Frontal Images Only
Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require ...
Akshay Asthana (Australian National University), R...
AAAI
2012
11 years 11 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
ICMCS
2006
IEEE
149views Multimedia» more  ICMCS 2006»
14 years 3 months ago
Video Texture and Motion based Modeling of Rate Variability-Distortion (VD) Curves of I, P, and B Frames
We examine the bit rate variability-distortion (VD) curve of I, P, and B frames of MPEG-4 VBR encoded video sequences. We show that the concave VD curve shape at high compression ...
Geert Van Der Auwera, Martin Reisslein, Lina J. Ka...