Interactive graph cut based segmentation with shape priors

• Published in: 2005 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
• Language: English
• 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
• DOI: 10.1109/CVPR.2005.191
• ISBN: 0769523722; 9780769523729
• ISSN: 1063-6919

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.