Level set based hippocampus segmentation in MR images with improved initialization using region growing
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Publication:2401094
DOI10.1155/2017/5256346zbMath1377.92052OpenAlexW2572934080WikidataQ37611335 ScholiaQ37611335MaRDI QIDQ2401094
Xiaoliang Jiang, Xiaolei Deng, Ling Zou, Bai-Lin Li, Xiaokang Ding, Zhaozhong Zhou
Publication date: 31 August 2017
Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2017/5256346
Applications of statistics to biology and medical sciences; meta analysis (62P10) Biomedical imaging and signal processing (92C55)
Cites Work
- A method for lung boundary correction using split Bregman method and geometric active contour model
- An active contour model based on adaptive threshold for extraction of cerebral vascular structures
- Probability density difference-based active contour for ultrasound image segmentation
- Generalized gradient vector flow external forces for active contours
- Geodesic active contours
- Optimal approximations by piecewise smooth functions and associated variational problems
- On active contour models and balloons
- Active contours without edges
- Variational Segmentation of Vector-Valued Images With Gradient Vector Flow
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