Deformable models in medical image analysis: a survey

TL;DR: An automatic 3-D segmentation method that fully exploits the prior knowledge about the shape of the membranes as well as the3-D information provided by the tomograms, and systematically combines this knowledge with the image data to improve segmentation results is developed.

TL;DR: A new geometric deformable surface model which preserves topology and an overall strategy for reconstructing the inner, central, and outer surfaces of the brain cortex is described, which is fast and numerically stable, and yields accurate brain surface reconstructions that are guaranteed to be topologically correct and free from self intersections.

TL;DR: Two different methods are established to propagate organ models through the image time series, one based on deformable surface meshes, and the other based on volumetric B-spline registration, which achieves good overall results.

TL;DR: The main focus of this paper is on measuring and tracking quantitative parameters for objective vocal fold functional assessment, from videokymographic examinations of subjects with normal and pathological laryngeal function, based on active contour search implemented with a properly adjusted robust snake algorithm.

TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.

TL;DR: A novel scheme for the detection of object boundaries based on active contours evolving in time according to intrinsic geometric measures of the image, allowing stable boundary detection when their gradients suffer from large variations, including gaps.

TL;DR: The decomposition of deformations by principal warps is demonstrated and the method is extended to deal with curving edges between landmarks to aid the extraction of features for analysis, comparison, and diagnosis of biological and medical images.

TL;DR: Wavelet and short-time Fourier analysis is introduced in the context of frequency decompositions, associating wavelet type decompositions with filter banks, and using filter bank theory to construct multiplicity M wavelet frames and tight frames.