3D Active Net, which is a 3D extension of Snakes, is an energy-minimizing surface model which can extract a volume of interest from 3D volume data. It is deformable and evolves in 3D space to be attracted to salient features, according to its internal and image energy. The net can be tted to the contour of a target object by the de nition of the image energy suitable for the contour property. I...

Contour extraction of image stacks is a basic task in medical modeling. The existing level-set methods usually suffer from some problems (e.g. serious errors around sharp features, incorrect split of topology and contour occlusions). This paper proposes a novel method of multi-constraint level-set evolution to avoid above-mentioned problems. Interpolation constraint and deviation constraint are...

Classic curvature-minimizing active contour models are often incapable of extracting complex shapes with points of high curvature. This paper presents a new active contour model which overcomes this problem and which can be applied to image segmentation as well as shape description in order to allow for quantitative and qualitative studies of shape measurements at multiple scales. Multiscale di...

Classic curvature-minimizing active contour models are often incapable of extracting complex shapes with points of high curvature. This paper presents a new active contour model which overcomes this problem and which can be applied to image segmentation as well as shape description in order to allow for quantitative and qualitative studies of shape measurements at multiple scales. Multiscale di...

The problem considered in this paper is how to recognize similar objects based on the detection of patterns in pairs of images. This article introduces a new form of classifier based on approximation spaces in the context of near sets for use in pattern recognition. By way of introducing the basic approach, nonlinear diffusion is used for edge detection and object contour extraction. This form ...

We propose a method for interactive boundary extraction which combines a deep, patch-based representation with an active contour framework. We train a class-specific convolutional neural network which predicts a vector pointing from the respective point on the evolving contour towards the closest point on the boundary of the object of interest. These predictions form a vector field which is the...

The same type of objects in different images may vary in their shapes because of rigid and non-rigid shape deformations, occluding foreground as well as cluttered background. The problem concerned in this work is the shape extraction in such challenging situations. We approach the shape extraction through shape alignment and recovery. This paper presents a novel and general method for shape ali...

Iris recognition is one of the most reliable and accurate biometric technologies, as the richness and apparent stability of the iris texture make it robust. Iris segmentation is a critical part in iris recognition, because it defines the inner and outer boundaries of iris region which is used for feature analysis. Active contour model, also known as snake, is a powerful image segmentation techn...

This paper proposes an active contour framework for spectrogram track detection. A potential energy is proposed which results in feature extraction at a signal-to-noise ratio (SNR) of 0.5 dB. We show, through complexity analysis, that this is achievable in real-time.

IEEE Computer Graphics and Applications 49 Cortical sulci are convoluted regions between cortical folds deeply embedded in the surface of the brain. Because of their significant characteristics, their functional separation of distinct brain regions, and their natural topological partition of anatomy, sulci serve as a basis for structural analysis of the brain. Thus they receive significant atte...