Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation

By Daniel Cremers, Stanley J. Osher, Stefano Soatto. International Journal of Computer Vision, 2006

389 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/2a78cc5db6993752408cf3d3b0edd8be3c6c9df7

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Citations in the corpus

GeoS: Geodesic Image Segmentation (2008, result): “Similar results are obtained on this image by imposing soft constraints on global statistics of appearance or shape (see also [30]).”
A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape (2007, background): “From left to right, the shape priors are a single static shape prior (Rousson and Paragios, 2002), uniformly distributed in the PCA subspace (Rousson, 2004), automatically selected from multiple shape instances (Cremers et al., 2006) and dynamical (Cremers, 2006).”
Graph Cuts and Efficient N-D Image Segmentation (2006, background): “The same basic idea is widely used in level-sets, e.g. (Cremers et al., 2006; Cremers, 2006).”
Dynamical statistical shape priors for level set-based tracking (2006, background): “However, although they can be applied to tracking objects in image sequences [8], [18], [9], they are not well-suited for this task because they neglect the temporal coherence of silhouettes which characterizes many deforming shapes.”
A Bayesian model of shape and appearance for subcortical brain segmentation (2011, neutral): “…as: region competition (Chupin et al., 2007, 2009); homotopic region deformation (Lehéricy et al., 2009); level-sets within a Bayesian framework (Cremers et al., 2006) or with local distribution models (Yan et al., 2004); 4D shape priors (Kohlberger et al., 2006); probabilistic boosting trees…”
A review of techniques for the identification and measurement of fish in underwater stereo-video image sequences (2013, background): “Candidates are identified based on frame difference images and a binary pattern classifier to locate the characteristic crescent shape of the fish heads.”
Object segmentation by alignment of poselet activations to image contours (2011, methodology): “Shape priors in image segmentation have become popular based on the work by Leventon et al. [15] and the line of works by Cremers et al. [8, 9].”
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support (2017, methodology): “The sensitivity encoder (SENSE) transforms the partial k-spaces into images, then merges the resulting aliased images into one coherent image [14].”
Star Shape Prior for Graph-Cut Image Segmentation (2008, methodology): “Using shape priors to improve segmentation has been investigated in the level set and curve evolution frameworks [18–21].”
A survey of graph theoretical approaches to image segmentation (2013, background): “[21,78] to specify the template as a distance function whose zero level set corresponds to the template.”