Interactive graph cut based segmentation with shape priors

Interactive or semi-automatic segmentation is a useful alternative to pure automatic segmentation in many applications. While automatic segmentation can be very challenging, a small amount of user input can often resolve ambiguous decisions on the part of the algorithm. In this work, we devise a gra...

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Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 755 - 762 vol. 1
Main Authors Freedman, D., Tao Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Application software
Biomedical applications of radiation
Biomedical imaging
Bladder
Computer science
graph cuts
Image segmentation
Level set
level sets
Medical treatment
segmentation
Shape
shape priors
Visualization
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Summary:Interactive or semi-automatic segmentation is a useful alternative to pure automatic segmentation in many applications. While automatic segmentation can be very challenging, a small amount of user input can often resolve ambiguous decisions on the part of the algorithm. In this work, we devise a graph cut algorithm for interactive segmentation which incorporates shape priors. While traditional graph cut approaches to interactive segmentation are often quite successful, they may fail in cases where there are diffuse edges, or multiple similar objects in close proximity to one another. Incorporation of shape priors within this framework mitigates these problems. Positive results on both medical and natural images are demonstrated.
ISBN:0769523722
9780769523729
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2005.191