Adaptive volumetric texture segmentation based on Gaussian Markov random fields features

[1]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[2]  R.M. Haralick,et al.  Statistical and structural approaches to texture , 1979, Proceedings of the IEEE.

[3]  B. Julesz Textons, the elements of texture perception, and their interactions , 1981, Nature.

[4]  Alexander A. Sawchuk,et al.  Supervised Textured Image Segmentation Using Feature Smoothing and Probabilistic Relaxation Techniques , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[6]  Bidyut Baran Chaudhuri,et al.  Texture Segmentation Using Fractal Dimension , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Jitendra Malik,et al.  Textons, contours and regions: cue integration in image segmentation , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[8]  Dinggang Shen,et al.  Automated Segmentation of 3D US Prostate Images Using Statistical Texture-Based Matching Method , 2003, MICCAI.

[9]  Dimitris N. Metaxas,et al.  A Novel Stochastic Combination of 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI , 2003, MICCAI.

[10]  Hamid Soltanian-Zadeh,et al.  Comparison of 2D and 3D wavelet features for TLE lateralization , 2004, SPIE Medical Imaging.

[11]  Jaime S. Cardoso,et al.  Toward a generic evaluation of image segmentation , 2005, IEEE Transactions on Image Processing.

[12]  Maria Petrou,et al.  Image processing - dealing with texture , 2020 .

[13]  A. Björkström Ridge Regression and inverse problems , 2007 .

[14]  Constantino Carlos Reyes-Aldasoro,et al.  Volumetric Texture Segmentation by Discriminant Feature Selection and Multiresolution Classification , 2007, IEEE Transactions on Medical Imaging.

[15]  Jean-Yves Ramel,et al.  Comparison between 2D and 3D Local Binary Pattern Methods for Characterisation of Three-Dimensional Textures , 2008, ICIAR.

[16]  Jean-Yves Ramel,et al.  A Solid Texture Database for Segmentation and Classification Experiments , 2009, VISAPP.

[17]  William Q. Meeker,et al.  A Comparison of Maximum Likelihood and Median-Rank Regression for Weibull Estimation , 2010 .

[18]  Baowei Fei,et al.  Automatic 3D segmentation of the kidney in MR images using wavelet feature extraction and probability shape model , 2012, Medical Imaging.

[19]  Yee-Hong Yang,et al.  Robust Volumetric Texture Classification of Magnetic Resonance Images of the Brain Using Local Frequency Descriptor , 2014, IEEE Transactions on Image Processing.

[20]  Sasan Mahmoodi,et al.  Gaussian Markov random field based improved texture descriptor for image segmentation , 2014, Image Vis. Comput..

[21]  Dimitri Van De Ville,et al.  Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities , 2014, Medical Image Anal..

[22]  Jean-Yves Ramel,et al.  A framework of perceptual features for the characterisation of 3D textured images , 2015, Signal Image Video Process..

[23]  Sasan Mahmoodi,et al.  Rotation invariant texture descriptors based on Gaussian Markov random fields for classification , 2016, Pattern Recognit. Lett..

[24]  Yu Li,et al.  A fuzzy clustering image segmentation algorithm based on Hidden Markov Random Field models and Voronoi Tessellation , 2017, Pattern Recognit. Lett..

[25]  Farshad Tajeripour,et al.  Detection of brain tumor in 3D MRI images using local binary patterns and histogram orientation gradient , 2017, Neurocomputing.

[26]  J. Wedzicha,et al.  Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease 2017 Report: GOLD Executive Summary , 2017, European Respiratory Journal.

[27]  Vincent Mazet,et al.  Oriented Triplet Markov Fields , 2018, Pattern Recognit. Lett..

[28]  Sasan Mahmoodi,et al.  Volumetric Texture Analysis Based on Three-Dimensional Gaussian Markov Random Fields for COPD Detection , 2018, MIUA.

[29]  Sasan Mahmoodi,et al.  Gaussian Markov Random Fields-Based Features for Volumetric Texture Segmentation , 2019, 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR).

[30]  Hasan F. Ates,et al.  Multi-hypothesis contextual modeling for semantic segmentation , 2019, Pattern Recognit. Lett..