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» A statistical framework for DTI segmentation
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ICIP
2006
IEEE
16 years 1 months ago
Using Non-Parametric Kernel to Segment and Smooth Images Simultaneously
Piecewise constant and piecewise smooth Mumford-Shah (MS) models have been widely studied and used for image segmentation. More complicated than piecewise constant MS, global Gaus...
Weihong Guo, Yunmei Chen
ECCV
2002
Springer
16 years 1 months ago
Probabilistic Search for Object Segmentation and Recognition
Abstract. The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range ...
Ulrich Hillenbrand, Gerd Hirzinger
MICCAI
2005
Springer
16 years 17 days ago
A Unifying Approach to Registration, Segmentation, and Intensity Correction
We present a statistical framework that combines the registration of an atlas with the segmentation of magnetic resonance images. We use an Expectation Maximization-based algorithm...
Kilian M. Pohl, John W. Fisher III, James J. Levit...
ICASSP
2010
IEEE
14 years 12 months ago
Convergence behavior of the Active Mask segmentation algorithm
We study the convergence behavior of the Active Mask (AM) framework, originally designed for segmenting punctate image patterns. AM combines the flexibility of traditional active...
Doru-Cristian Balcan, Gowri Srinivasa, Matthew C. ...
CVPR
1999
IEEE
16 years 1 months ago
Histogram Clustering for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann