GMM based simultaneous reconstruction and segmentation in X-ray CT application

DOI10.1007/978-3-030-75549-2_40zbMath1497.65053OpenAlexW3157303990WikidataQ107752256 ScholiaQ107752256MaRDI QIDQ826217

Yiqiu Dong, Shi Yan

Publication date: 20 December 2021

Full work available at URL: https://doi.org/10.1007/978-3-030-75549-2_40

zbMATH Keywords

inverse problemGaussian mixture modelalternating minimisation methodsimultaneous reconstruction and segmentationX-ray CT

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

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• Nonlinear total variation based noise removal algorithms
• A Mumford-Shah level-set approach for the inversion and segmentation of X-ray tomography data
• A dual EM algorithm for TV regularized Gaussian mixture model in image segmentation
• AIR tools -- a MATLAB package of algebraic iterative reconstruction methods
• Simultaneous tomographic reconstruction and segmentation with class priors
• Optimal approximations by piecewise smooth functions and associated variational problems
• Joint image reconstruction and segmentation using the Potts model
• A Weighted Dictionary Learning Model for Denoising Images Corrupted by Mixed Noise
• Enhancing joint reconstruction and segmentation with non-convex Bregman iteration
• The Radon Transform and Medical Imaging
• User-Friendly Simultaneous Tomographic Reconstruction and Segmentation with Class Priors
• Convergence of a block coordinate descent method for nondifferentiable minimization

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