A variational level set approach based on local entropy for image segmentation and bias field correction

DOI10.1155/2017/9174275zbMath1409.92141OpenAlexW2769885143WikidataQ47106321 ScholiaQ47106321MaRDI QIDQ1731282

Xiaoliang Jiang, Jian Tang

Publication date: 13 March 2019

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/9174275

zbMATH Keywords

local entropymedical image segmentationbias field correction

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Measures of information, entropy (94A17)

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Cites Work

• A Mathematical Theory of Communication
• Probability density difference-based active contour for ultrasound image segmentation
• Active contours driven by local Gaussian distribution fitting energy
• An improved hybrid gradient variation level set method for image segmentation and bias correction
• Minimization of Region-Scalable Fitting Energy for Image Segmentation
• A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI

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