Seeded Segmentation Methods for Medical Image Analysis

Abstract : Segmentation is one of the key tools in medical image analysis. The objective of segmentation is to provide reliable, fast, and effective organ delineation. While traditionally, particularly in computer vision, segmentation is seen as an early vision tool used for subsequent recognition, in medical imaging the opposite is often true. Recognition can be performed interactively by clinicians or automatically using robust techniques, while the objective of segmentation is to precisely delineate contours and surfaces. This can lead to effective techniques known as "intelligent scissors" in 2D and their equivalent in 3D.
Liste complète des métadonnées

Cited literature [67 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00715457
Contributor : Laurent Najman <>
Submitted on : Saturday, July 7, 2012 - 1:43:48 PM
Last modification on : Thursday, July 5, 2018 - 2:25:52 PM
Document(s) archivé(s) le : Monday, October 8, 2012 - 2:21:05 AM

File

outfile_p44-p75.pdf
Files produced by the author(s)

Identifiers

Citation

Camille Couprie, Laurent Najman, Hugues Talbot. Seeded Segmentation Methods for Medical Image Analysis. Dougherty, Geoff. Medical Image Processing, Springer New York, pp.27-57, 2011, Biological and Medical Physics, Biomedical Engineering, 978-1-4419-9779-1. ⟨10.1007/978-1-4419-9779-1_3⟩. ⟨hal-00715457⟩

Share

Metrics

Record views

326

Files downloads

433