Fast extraction of minimal paths in 3D images and applications to virtual endoscopy

By T. Deschamps, Laurent D. Cohen. Medical Image Anal., 2001

421 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/ee15e56872ccc49e73e63dc1691841969063c7de

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In Computer Vision and Pattern Recognition

In Ocean Engineering

Citations in the corpus

Velocity analysis using AB semblance (2009, methodology): “An analogous approach has been used in medical imaging in the method of virtual endoscopy (Deschamps and Cohen 2001).”
Computer analysis of computed tomography scans of the lung: a survey (2006, positive): “up into four main strategies: (i) knowledge-based segmentation [19], [20]; (ii) region growing/wave propagation [19], [20], [22], [25], [27]–[33], [40]; (iii) centreline extraction [23], [24], [26]; (iv) mathematical morphology [25], [41], [42].”
Computer Methods and Programs in Biomedicine (neutral): “The work proposed in [192] is employable on 2D structures, while further extensions introduced in [193,194] lead to the segmentation of 3D structure.”
A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes (2009, background): “, computing paths from the start and end points simultaneously, considerably lowers computational costs (Deschamps and Cohen, 2001; Olabarriaga et al., 2003; Wink et al., 2000b).”
Digital Topology and Geometry in Medical Imaging: A Survey (2015, methodology): “Cohen [227] used the minimal path approach to find multiple contours in an image from an unstructured set of edge points.”
Graph cut based image segmentation with connectivity priors (2008, methodology): “(A fast marching technique was used in [5], which can be viewed as a continuous analogue of the Dijkstra algorithm for discrete graphs.”
SEMANTIC SEGMENTATION OF AERIAL IMAGES IN URBAN AREAS WITH CLASS-SPECIFIC HIGHER-ORDER CLIQUES (2015, methodology): “Second, minimum cost paths through the volume are computed with the 3D Fast Marching algorithm (Deschamps and Cohen, 2001) to connect road likelihoods to elongated paths.”
Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection (2016, methodology): “By considering images as connected graph of pixels, minimal path extraction has been used for a number of applications in image processing such as segmentation or medical images [28], road extraction in satellite images [29] or object boundary extraction [30].”