International audienceThis paper proposes a novel approach that allows regionbased active contour energy to be re-expressed combining local and global information. The basic idea of this technique consists in extracting image statistics locally from the heterogeneous region (foreground or background) and globally from the other region at each point along the curve. By exploiting benefits of both local-based and global-based statistics, this technique proves to be robust against heterogeneity and noise and shows low sensitivity to curve initialization. Experimental results for synthetic and real images reveal significant improvement compared to conventional methods
Abstract Segmenting the region of interest (ROI) from medical images is a fundamental but challengin...
International audienceThis article deals with statistical region-based active contour segmentation u...
Image inhomogeneity often occurs in real-world images and may present considerable difficulties duri...
International audienceThis paper proposes a novel approach that allows regionbased active contour en...
©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish thi...
International audienceIn this paper, we propose a new approach using a local version of the region-b...
Global region-based active contours, like the Chan-Vese model, often make strong assumptions on the ...
International audienceLocal region-based active contours using Gauss smooth function to approximate ...
Active contour models are always designed on the assumption that images are approximated by regions ...
This paper presents a local- and global-statistics-based active contour model for image segmentation...
This paper introduces an improved region based active contour method with a level set formulation. T...
This article introduces a new image segmentation method that makes use of non-local comparisons betw...
Intensity nonuniformity is one of the common issues in image segmentation, which is caused by techni...
International audienceThe variational method has been introduced by Kass et al. (1987) in the field ...
AbstractThis paper presents an improved active contour model by combining the Chan–Vese model, the r...
Abstract Segmenting the region of interest (ROI) from medical images is a fundamental but challengin...
International audienceThis article deals with statistical region-based active contour segmentation u...
Image inhomogeneity often occurs in real-world images and may present considerable difficulties duri...
International audienceThis paper proposes a novel approach that allows regionbased active contour en...
©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish thi...
International audienceIn this paper, we propose a new approach using a local version of the region-b...
Global region-based active contours, like the Chan-Vese model, often make strong assumptions on the ...
International audienceLocal region-based active contours using Gauss smooth function to approximate ...
Active contour models are always designed on the assumption that images are approximated by regions ...
This paper presents a local- and global-statistics-based active contour model for image segmentation...
This paper introduces an improved region based active contour method with a level set formulation. T...
This article introduces a new image segmentation method that makes use of non-local comparisons betw...
Intensity nonuniformity is one of the common issues in image segmentation, which is caused by techni...
International audienceThe variational method has been introduced by Kass et al. (1987) in the field ...
AbstractThis paper presents an improved active contour model by combining the Chan–Vese model, the r...
Abstract Segmenting the region of interest (ROI) from medical images is a fundamental but challengin...
International audienceThis article deals with statistical region-based active contour segmentation u...
Image inhomogeneity often occurs in real-world images and may present considerable difficulties duri...