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» A Markov Random Field Model for Medical Image Denoising
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ICIP
2009
IEEE
15 years 3 months ago
Fluorescence diffuse optical image reconstruction with a priori information
This paper addresses fluorescence diffuse optical tomography (FDOT) reconstruction problem with a priori information. We assume that approximate location of the fluorophore concen...
Lu Zhou, An Jin, Birsen Yazici
CVPR
2008
IEEE
16 years 8 months ago
Auto-context and its application to high-level vision tasks
The notion of using context information for solving highlevel vision problems has been increasingly realized in the field. However, how to learn an effective and efficient context...
Zhuowen Tu
ECCV
2006
Springer
16 years 8 months ago
Smooth Image Segmentation by Nonparametric Bayesian Inference
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
Peter Orbanz, Joachim M. Buhmann
MICCAI
2010
Springer
15 years 4 months ago
Non-parametric Iterative Model Constraint Graph min-cut for Automatic Kidney Segmentation
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori es...
Moti Freiman, A. Kronman, S. J. Esses, Leo Joskowi...
CVPR
2006
IEEE
16 years 7 days ago
Combined Depth and Outlier Estimation in Multi-View Stereo
In this paper, we present a generative model based approach to solve the multi-view stereo problem. The input images are considered to be generated by either one of two processes:...
Christoph Strecha, Rik Fransens, Luc J. Van Gool