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» Supervised Image Segmentation Using Markov Random Fields
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MICCAI
2003
Springer
15 years 10 months ago
Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach
Abstract. In this paper we propose a novel non-Gaussian MRF for regularization of tensor fields for fiber tract enhancement. Two entities are considered in the model, namely, the l...
Marcos Martín-Fernández, Carlos Albe...
56
Voted
ICIP
2006
IEEE
15 years 3 months ago
Discontinuity-Adaptive De-Interlacing Scheme Using Markov Random Field Model
— In this paper, a de-interlacing algorithm to find the optimal deinterlaced results given accuracy-limited motion information is proposed. The de-interlacing process is formula...
Min Li, Truong Q. Nguyen
78
Voted
MICCAI
2009
Springer
15 years 10 months ago
A Fully Automatic Random Walker Segmentation for Skin Lesions in a Supervised Setting
Abstract. We present a method for automatically segmenting skin lesions by initializing the random walker algorithm with seed points whose properties, such as colour and texture, h...
Paul Wighton, Maryam Sadeghi, Tim K. Lee, M. St...
98
Voted
NIPS
2008
14 years 11 months ago
Multiscale Random Fields with Application to Contour Grouping
We introduce a new interpretation of multiscale random fields (MSRFs) that admits efficient optimization in the framework of regular (single level) random fields (RFs). It is base...
Longin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang ...
ICIP
2003
IEEE
15 years 11 months ago
Object localization using texture motifs and Markov random fields
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath