T-snakes: Topology adaptive snakes

By Tim McInerney, Demetri Terzopoulos. Medical Image Anal., 2000

510 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Biophysics, Geometry and Topology

View Paper: https://www.semanticscholar.org/paper/6bbdb8e452d775a5efcd1b253af72df2c42cf8f9

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In Biomedical Engineering

In Biophysics

In Geometry and Topology

Citations in the corpus

A Topology Preserving Level Set Method for Geometric Deformable Models (2003, background): “Third, the propagating contour can automatically change topology in geometric models (e.g., merge or split) without requiring an elaborate mechanism to handle such changes as in parametric models (see [19], [20]).”
Flux maximizing geometric flows (2001, methodology): “These models have been applied with some success to the segmentation of angiography as well as other forms of medical data and extensions to 3D have been developed [28], [27].”
Ridge-based vessel segmentation in color images of the retina (2004, methodology): “The first group consists of rule-based methods and comprises vessel tracking [8]–[11], matched filter responses [1], [12], [13], grouping of edge pixels [14], model based locally adaptive thresholding [2], topology adaptive snakes [15] and morphology-based techniques [16]–[18].”
Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification (2005, methodology): “The use of deformable models also shows promising results in [19]–[22].”
A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features (2011, methodology): “On the other hand, deformable or snake models have been also used in [44] and [45].”
Segmentation and Shape Tracking of Whole Fluorescent Cells Based on the Chan–Vese Model (2013, background): “out the detection of multiple isolated objects from a single initial contour unless special surgical routines are used [43], [44].”