Abstract
The telemedicine concept integrates images, video acquisition and video transfer which are usually managed by using a standard videoconference system. Very often, the initial blur of echography pictures makes it difficult to use standard segmentation techniques such as snakes or Sobel filters which aid the doctor in making his decision. In medical echography practice, contour properties of an organ are often more relevant to decipher the presence of pathologies than the exact lineout of the contour itself. The processing, via the fuzzy approach, enables us to subdivide an image in different classes: one gathering the homogeneous zones (pixels belonging to a medium) and the other gathering more heterogeneous zones (e.g. transition between two media). Complexity measurement of each region can be approximated by the calculation of a fractal dimension. Thus, we can obtain interface complexity without having to extract the interfaces themselves. Finally, the link between fractal dimension and fuzzy rate is carried out.
Capri, Arnaud;
[1]
SINTERS GROUP SAS, 5 rue Paul Mesple, BP 1311, 31106 ToulouseCedex 01 (France)]. E-mail: Arnaud.Capri@bourges.univ-orleans.fr;
Vincent, Nicole;
[2]
Vieyres, Pierre;
[1]
Poisson, Gerard;
[1]
Makris, Pascal
[3]
- LVR, Orleans University, IUT de Bourges, 63 avenue de Lattre de Tassigny, 18020 Bourges (France)
- CRIP5-SIP, Rene Descartes University-Paris 5, 45 rue des Saints-Peres, 75270 Paris Cedex 06 (France)
- LI, University Francois Rabelais of Tours, 64 avenue Jean Portalis, 37200 Tours (France)
Citation Formats
Capri, Arnaud, SINTERS GROUP SAS, 5 rue Paul Mesple, BP 1311, 31106 ToulouseCedex 01 (France)]. E-mail: Arnaud.Capri@bourges.univ-orleans.fr, Vincent, Nicole, Vieyres, Pierre, Poisson, Gerard, and Makris, Pascal.
Interface areas complexity characterization of echographic images.
Netherlands: N. p.,
2006.
Web.
doi:10.1016/j.nima.2006.08.120.
Capri, Arnaud, SINTERS GROUP SAS, 5 rue Paul Mesple, BP 1311, 31106 ToulouseCedex 01 (France)]. E-mail: Arnaud.Capri@bourges.univ-orleans.fr, Vincent, Nicole, Vieyres, Pierre, Poisson, Gerard, & Makris, Pascal.
Interface areas complexity characterization of echographic images.
Netherlands.
https://doi.org/10.1016/j.nima.2006.08.120
Capri, Arnaud, SINTERS GROUP SAS, 5 rue Paul Mesple, BP 1311, 31106 ToulouseCedex 01 (France)]. E-mail: Arnaud.Capri@bourges.univ-orleans.fr, Vincent, Nicole, Vieyres, Pierre, Poisson, Gerard, and Makris, Pascal.
2006.
"Interface areas complexity characterization of echographic images."
Netherlands.
https://doi.org/10.1016/j.nima.2006.08.120.
@misc{etde_20870422,
title = {Interface areas complexity characterization of echographic images}
author = {Capri, Arnaud, SINTERS GROUP SAS, 5 rue Paul Mesple, BP 1311, 31106 ToulouseCedex 01 (France)]. E-mail: Arnaud.Capri@bourges.univ-orleans.fr, Vincent, Nicole, Vieyres, Pierre, Poisson, Gerard, and Makris, Pascal}
abstractNote = {The telemedicine concept integrates images, video acquisition and video transfer which are usually managed by using a standard videoconference system. Very often, the initial blur of echography pictures makes it difficult to use standard segmentation techniques such as snakes or Sobel filters which aid the doctor in making his decision. In medical echography practice, contour properties of an organ are often more relevant to decipher the presence of pathologies than the exact lineout of the contour itself. The processing, via the fuzzy approach, enables us to subdivide an image in different classes: one gathering the homogeneous zones (pixels belonging to a medium) and the other gathering more heterogeneous zones (e.g. transition between two media). Complexity measurement of each region can be approximated by the calculation of a fractal dimension. Thus, we can obtain interface complexity without having to extract the interfaces themselves. Finally, the link between fractal dimension and fuzzy rate is carried out.}
doi = {10.1016/j.nima.2006.08.120}
journal = []
issue = {2}
volume = {569}
place = {Netherlands}
year = {2006}
month = {Dec}
}
title = {Interface areas complexity characterization of echographic images}
author = {Capri, Arnaud, SINTERS GROUP SAS, 5 rue Paul Mesple, BP 1311, 31106 ToulouseCedex 01 (France)]. E-mail: Arnaud.Capri@bourges.univ-orleans.fr, Vincent, Nicole, Vieyres, Pierre, Poisson, Gerard, and Makris, Pascal}
abstractNote = {The telemedicine concept integrates images, video acquisition and video transfer which are usually managed by using a standard videoconference system. Very often, the initial blur of echography pictures makes it difficult to use standard segmentation techniques such as snakes or Sobel filters which aid the doctor in making his decision. In medical echography practice, contour properties of an organ are often more relevant to decipher the presence of pathologies than the exact lineout of the contour itself. The processing, via the fuzzy approach, enables us to subdivide an image in different classes: one gathering the homogeneous zones (pixels belonging to a medium) and the other gathering more heterogeneous zones (e.g. transition between two media). Complexity measurement of each region can be approximated by the calculation of a fractal dimension. Thus, we can obtain interface complexity without having to extract the interfaces themselves. Finally, the link between fractal dimension and fuzzy rate is carried out.}
doi = {10.1016/j.nima.2006.08.120}
journal = []
issue = {2}
volume = {569}
place = {Netherlands}
year = {2006}
month = {Dec}
}