Image segmentation with dynamic artifacts detection and bias correction

DOI10.3934/ipi.2017027zbMath1407.68524OpenAlexW2610036018WikidataQ58466984 ScholiaQ58466984MaRDI QIDQ524736

Liane S. Slaughter, Jing An, Paul S. Weiss, Morgan Weiss, Nicholas Takaki, Andrea L. Bertozzi, James Stevick, Dominique Zosso, Huanhuan Cao

Publication date: 3 May 2017

Published in: Inverse Problems and Imaging (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/ipi.2017027

zbMATH Keywords

biasthreshold dynamicslevel-set methodimage segmentationartifactsChan-Vese modeldynamic labelingMBOretinex

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (9)

A minimal surface criterion for graph partitioning ⋮ A Retinex-based total variation approach for image segmentation and bias correction ⋮ A new effective bias field correction model with TGV regularization ⋮ Image segmentation based on the hybrid bias field correction ⋮ A Retinex-based selective segmentation model for inhomogeneous images ⋮ An Active Contour Model with Local Variance Force Term and Its Efficient Minimization Solver for Multiphase Image Segmentation ⋮ Two-dimensional compact variational mode decomposition ⋮ Multiscale Segmentation via Bregman Distances and Nonlinear Spectral Analysis ⋮ Two-Phase Segmentation for Intensity Inhomogeneous Images by the Allen--Cahn Local Binary Fitting Model

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