MCMC algorithm based on Markov random field in image segmentation. [PDF]
PLoS ONEIn the realm of digital image applications, image processing technology occupies a pivotal position, with image segmentation serving as a foundational component.
Huazhe Wang, Li Ma
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Markov random field segmentation for industrial computed tomography with metal artefacts. [PDF]
J Xray Sci Technol, 2018 X-ray Computed Tomography (XCT) has become an important tool for industrial measurement and quality control through its ability to measure internal structures and volumetric defects.
Jaiswal A +4 more
europepmc +3 more sources
Constructing tissue-specific transcriptional regulatory networks via a Markov random field [PDF]
BMC Genomics, 2018 Background Recent advances in sequencing technologies have enabled parallel assays of chromatin accessibility and gene expression for major human cell lines.
Shining Ma, Tao Jiang, Rui Jiang
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Multiple testing for neuroimaging via hidden Markov random field. [PDF]
Biometrics, 2015 Traditional voxel-level multiple testing procedures in neuroimaging, mostly $p$-value based, often ignore the spatial correlations among neighboring voxels and thus suffer from substantial loss of power.
Shu H, Nan B, Koeppe R.
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Markov Random Field Surface Reconstruction [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2010 A method for implicit surface reconstruction is proposed. The novelty in this paper is the adaptation of Markov Random Field regularization of a distance field. The Markov Random Field formulation allows us to integrate both knowledge about the type of surface we wish to reconstruct (the prior) and knowledge about data (the observation model) in an ...
Bærentzen, Jakob Andreas +2 more
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MRI Reconstruction Using Markov Random Field and Total Variation as Composite Prior [PDF]
Sensors, 2020 Reconstruction of magnetic resonance images (MRI) benefits from incorporating a priori knowledge about statistical dependencies among the representation coefficients.
Marko Panić +4 more
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A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data [PDF]
BMC Bioinformatics, 2021 Background Recent development of single cell sequencing technologies has made it possible to identify genes with different expression (DE) levels at the cell type level between different groups of samples.
Hongyu Li +5 more
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SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGERY USING OBJECT-BASED MARKOV RANDOM FIELD BASED ON HIERARCHICAL SEGMENTATION TREE WITH AUXILIARY LABELS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 In the remote sensing imagery, spectral and texture features are always complex due to different landscapes, which leads to misclassifications in the results of semantic segmentation. The object-based Markov random field provides an effective solution to
L. He, Z. Wu, Y. Zhang, Z. Hu
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Random Fields in Physics, Biology and Data Science
Frontiers in Physics, 2021 A random field is the representation of the joint probability distribution for a set of random variables. Markov fields, in particular, have a long standing tradition as the theoretical foundation of many applications in statistical physics and ...
Enrique Hernández-Lemus +1 more
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One-dimensional Markov random fields, Markov chains and topological Markov fields [PDF]
Proceedings of the American Mathematical Society, 2013 15 ...
Marcus, B +4 more
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