DocumentCode
71972
Title
Spline-Based Deforming Ellipsoids for Interactive 3D Bioimage Segmentation
Author
Delgado-Gonzalo, Ricard ; Chenouard, Nicolas ; Unser, Michael
Author_Institution
Biomed. Imaging Group, Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
Volume
22
Issue
10
fYear
2013
fDate
Oct. 2013
Firstpage
3926
Lastpage
3940
Abstract
We present a new fast active-contour model (a.k.a. snake) for image segmentation in 3D microscopy. We introduce a parametric design that relies on exponential B-spline bases and allows us to build snakes that are able to reproduce ellipsoids. We design our bases to have the shortest-possible support, subject to some constraints. Thus, computational efficiency is maximized. The proposed 3D snake can approximate blob-like objects with good accuracy and can perfectly reproduce spheres and ellipsoids, irrespective of their position and orientation. The optimization process is remarkably fast due to the use of Gauss´ theorem within our energy computation scheme. Our technique yields successful segmentation results, even for challenging data where object contours are not well defined. This is due to our parametric approach that allows one to favor prior shapes. In addition, this paper provides a software that gives full control over the snakes via an intuitive manipulation of few control points.
Keywords
Gaussian processes; edge detection; image segmentation; medical image processing; optimisation; splines (mathematics); 3D microscopy; 3D snake; Gauss theorem; blob-like objects; computational efficiency; energy computation scheme; exponential B-spline bases; fast active-contour model; image segmentation; interactive 3D bioimage segmentation; object contours; optimization process; parametric design; spline-based deforming ellipsoids; 3D; Active contour; active surface; ellipsoid; exponential B-spline; microscopy; parameterization; parametric snake; segmentation; sphere; Algorithms; Animals; Brain; Diagnostic Imaging; Imaging, Three-Dimensional; Mice; Microscopy, Confocal; Spleen; Tomography, X-Ray Computed;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2013.2264680
Filename
6518128
Link To Document