Active contour model driven by global and local intensity information for ultrasound image segmentation

DOI10.1016/j.camwa.2018.03.029zbMath1417.92080OpenAlexW2797508642MaRDI QIDQ2001337

Lingling Fang, Chaofeng Chen, Yin Liu, Tian-shuang Qiu

Publication date: 3 July 2019

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2018.03.029

zbMATH Keywords

partial differential equationsactive contourultrasound image segmentationvector image segmentation

Mathematics Subject Classification ID

Biomedical imaging and signal processing (92C55) PDEs in connection with biology, chemistry and other natural sciences (35Q92) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (3)

Automatic ultrasound image segmentation based on local entropy and active contour model ⋮ Mesh free alternate directional implicit method based three dimensional super-diffusive model for benign brain tumor segmentation ⋮ Active contour model based on improved fuzzy c-means algorithm and adaptive functions

Cites Work

• Unnamed Item
• Split Bregman method for minimization of improved active contour model combining local and global information dynamically
• On local region models and a statistical interpretation of the piecewise smooth Mumford-Shah functional
• Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
• Active contours without edges
• Localizing Region-Based Active Contours
• A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI

This page was built for publication: Active contour model driven by global and local intensity information for ultrasound image segmentation