MAC: Magnetostatic Active Contour Model

Authors:
Xianghua Xie;Majid Mirmehdi
Affiliations:
IEEE;IEEE
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2008

Citing 0
Cited 20

External Force for Active Contours: Gradient Vector Convolution

PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Stabilization of parametric active contours using a tangential redistribution term

IEEE Transactions on Image Processing
Geometric attraction-driven flow for image segmentation and boundary detection

Journal of Visual Communication and Image Representation
Computer-aided prognosis of ER+breast cancer histopathology and correlating survival outcome with oncotype DX assay

ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Segmentation and classification of triple negative breast cancers using DCE-MRI

ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Curvelet-based geodesic snakes for image segmentation with multiple objects

Pattern Recognition Letters
A nonconservative flow field for robust variational image segmentation

IEEE Transactions on Image Processing
Active contouring based on gradient vector interaction and constrained level set diffusion

IEEE Transactions on Image Processing
Modeling and Estimation of the Dynamics of Planar Algebraic Curves via Riccati Equations

Journal of Mathematical Imaging and Vision
Radial basis function based level set interpolation and evolution for deformable modelling

Image and Vision Computing
On real time active contours

Proceedings of the 48th Annual Southeast Regional Conference
Adaptive smoothness based robust active contours

Image and Vision Computing
Image segmentation based on the integration of colour-texture descriptors-A review

Pattern Recognition
A new active contour model based on the Conscience, Archiving and Mean-Movement mechanisms and the SOM

Pattern Recognition Letters
A shape prior constraint for implicit active contours

Pattern Recognition Letters
Coupling edge and region-based information for boundary finding in biomedical imagery

Pattern Recognition
Variational nonlocal image segmentation using split-Bregman

Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Active contour model driven by local histogram fitting energy

Pattern Recognition Letters
Efficient geometrical potential force computation for deformable model segmentation

MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
Adaptive diffusion flow active contours for image segmentation

Computer Vision and Image Understanding

Quantified Score

Hi-index	0.15

Visualization

Abstract

We propose an active contour model using an external force field that is based on magnetostatics and hypothesized magnetic interactions between the active contour and object boundaries. The major contribution of the method is that the interaction of its forces can greatly improve the active contour in capturing complex geometries and dealing with difficult initializations, weak edges and broken boundaries. The proposed method is shown to achieve significant improvements when compared against six well-known and state-of- he-art shape recovery methods, including the geodesic snake, the generalized version of GVF snake, the combined geodesic and GVF snake, and the charged particle model.