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» A Markov Random Field Model for Medical Image Denoising
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ICDAR
2011
IEEE
14 years 5 months ago
A Handwritten Character Extraction Algorithm for Multi-language Document Image
—In this paper, we propose a novel method for extracting handwritten characters from multi-language document images, which may contain various types of characters, e.g. Chinese, ...
Yonghong Song, Guilin Xiao, Yuanlin Zhang, Lei Yan...
MICCAI
2009
Springer
16 years 7 months ago
Probabilistic Region Matching in Narrow-Band Endoscopy for Targeted Optical Biopsy
Recent advances in biophotonics have enabled in-vivo, in-situ histopathology for routine clinical applications. The non-invasive nature of these optical `biopsy' techniques, h...
Selen Atasoy, Ben Glocker, Stamatia Giannarou, ...
MICCAI
2000
Springer
15 years 9 months ago
Fusing Speed and Phase Information for Vascular Segmentation in Phase Contrast MR Angiograms
This paper presents a statistical approach to aggregating speed and phase (directional) information for vascular segmentation in phase contrast magnetic resonance angiograms (PC-MR...
Albert C. S. Chung, J. Alison Noble, Paul E. Summe...
IPMI
2005
Springer
16 years 7 months ago
From Spatial Regularization to Anatomical Priors in fMRI Analysis
In this paper, we study Markov Random Fields as spatial smoothing priors in fMRI detection. Relatively high noise in fMRI images presents a serious challenge for the detection algo...
Wanmei Ou, Polina Golland
PAMI
2002
108views more  PAMI 2002»
15 years 5 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery