Image Segmentation Using Deformable Models

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PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques (2010, background): “The active models move (deform) under the influence of so-called internal force-like equations, which represent the curve or the surface bending characteristics, or so-called external forces, which are computed from the image data, typically as directional gradients [107, 108].”
On the relationship between parametric and geometric active contours (2000, background): “Many types of external forces have been developed in the past (see [41] for a comprehensive list of external forces), including the well-known pressure force [3] and the Gaussian potential force [1].”
Implicit Active Contours Driven by Local Binary Fitting Energy (2007, background): “First, active contour models can achieve sub-pixel accuracy of the object boundaries [18].”
Computer Methods and Programs in Biomedicine (unknown): “According to the representation of S , edge-based deformable models can be classiﬁed in parametric or geometric models [159] .”
Active contours driven by local Gaussian distribution fitting energy (2009, background): “In addition, images are often corrupted by various noises that challenge the segmentation [24].”