Title
Automatic Segmentation Of The Lungs Using Multiple Active Contours And Outlier Model
Abstract
This paper presents a method for the automatic segmentation of the lungs in X-ray computed tomography (CT) images. The proposed technique is based on the use of multiple active contour models (ACMs) for the simultaneous segmentation of both lungs and outlier detection. The technique starts by grey-level thresholding of the images followed by edge detection. Then the edge points are organized in strokes and a set of weights summing to one is assigned to each stroke. These weights represent the soft assignment of the stroke to each of the ACMs and depend on the distance between the stroke points and the ACM units, on gradient direction information and also on the stroke size. Both the weights and the ACMs energy minimization are computed using the generalized expectationmaximization (EM) algorithm. Initialization of the ACM's is fully automatic. Experimental results show the effectiveness of the proposed technique.
Year
DOI
Venue
2006
10.1109/IEMBS.2006.260185
2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15
Keywords
DocType
Volume
active contour,outlier detection,em algorithm,active contour model,energy minimization,image segmentation,edge detection
Conference
1
ISSN
Citations 
PageRank 
1557-170X
6
0.60
References 
Authors
12
2
Name
Order
Citations
PageRank
Margarida Silveira110910.48
Jorge Marques2221.90