Automated robust image segmentation: level set method using nonnegative matrix factorization with application to brain MRI

DOI10.1007/S11538-016-0190-0zbMath1361.92044OpenAlexW2461805532WikidataQ48622948 ScholiaQ48622948MaRDI QIDQ517989

Hassan M. Fathallah-Shaykh, Dimah Dera, Nidhal Bouaynaya

Publication date: 28 March 2017

Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11538-016-0190-0

zbMATH Keywords

NMFimage segmentationMRILSMintensity inhomogeneity

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• FSL

Cites Work

• Geodesic active contours
• Active contours driven by local Gaussian distribution fitting energy
• Active contours without edges
• Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification
• Minimization of Region-Scalable Fitting Energy for Image Segmentation
• Texture Classification Using Refined Histogram
• Framelet Algorithms for De-Blurring Images Corrupted by Impulse Plus Gaussian Noise

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