Search results for: Dongxiao Zhou

Items from 1 to 5 out of 5 results

article

Relative cerebral blood volume is a potential biomarker in late delayed radiation‐induced brain injury

Ying Xie, Haiwei Huang, Junjie Guo, Dongxiao Zhou

Journal of Magnetic Resonance Imaging > 47 > 4 > 1112 - 1118

Purpose To assess whether relative cerebral blood volume (rCBV) can provide information to reliably evaluate the stages of late delayed radiation‐induced brain injury. Materials and Methods Forty patients diagnosed with late delayed radiation‐induced brain injury were enrolled. The patients were examined using a 1.5T magnetic resonance imaging (MRI) system equipped with an 8‐channel head coil....

chapter

Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model

Georgy Gimel'farb, Dongxiao Zhou

Studies in Computational Intelligence > Applied Pattern Recognition > Special Applications > 221-245

A number of applied problems are effectively solved with simple Markov-Gibbs random field (MGRF) models of spatially homogeneous or piecewise-homogeneous images provided that their identification (parameter estimation) is able to focus such a prior on a particular class of images. We propose more accurate analytical potential estimates for a generic MGRF with multiple pairwise pixel interaction and use them for structural analysis and synthesis of stochastic and periodic image textures....

chapter

Geometric Structure and Randomness in Texture Analysis and Synthesis

Georgy Gimel’farb, Linjiang Yu, Dongxiao Zhou

Lecture Notes in Computer Science > Geometry, Morphology, and Computational Imaging > 120-140

Gibbs random field models describe image textures in terms of geometric structure and energy of pixel interactions. The interaction means statistical interdependence of signals, the structure is given by characteristic pixel neighbourhoods, and the energy depends on signal co- occurrences over the neighbourhoods. In translation invariant textures all the neighbourhoods have the same relative geometry...

chapter

Bunch Sampling for Fast Texture Synthesis

Dongxiao Zhou, Georgy Gimel’farb

Lecture Notes in Computer Science > Computer Analysis of Images and Patterns > Analysis and Understanding > 124-131

A fast technique for synthesising large-size spatially homogeneous textures is described. It randomly samples specific continuous or disjoint signal bunches from a given small-size training image. The bunches are replicated and randomly placed into the goal texture with due account of their interdependence. Both the geometric form of and placement rules for the bunches are estimated from the training...

chapter

Accurate Identification of a Markov-Gibbs Model for Texture Synthesis by Bunch Sampling

Georgy Gimel’farb, Dongxiao Zhou

Lecture Notes in Computer Science > Computer Analysis of Images and Patterns > Features and Classification > 979-986

A prior probability model is adapted to a class of images by identification, or parameter estimation from training data. We propose a new and accurate analytical identification of a generic Markov-Gibbs random field (MGRF) model with multiple pairwise interaction and use it for structural analysis and synthesis of textures.

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Search results for: Dongxiao Zhou

Relative cerebral blood volume is a potential biomarker in late delayed radiation‐induced brain injury

Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model

Geometric Structure and Randomness in Texture Analysis and Synthesis

Bunch Sampling for Fast Texture Synthesis

Accurate Identification of a Markov-Gibbs Model for Texture Synthesis by Bunch Sampling

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