Interactive graph cut based segmentation with shape priors. Freedman, D. & Zhang, T. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), volume 1, pages 755–762 vol. 1, June, 2005. doi abstract bibtex 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.
@inproceedings{freedman_interactive_2005,
title = {Interactive graph cut based segmentation with shape priors},
volume = {1},
doi = {10.1109/CVPR.2005.191},
abstract = {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.},
booktitle = {2005 {IEEE} {Computer} {Society} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR}'05)},
author = {Freedman, D. and Zhang, Tao},
month = jun,
year = {2005},
keywords = {Application software, Biomedical applications of radiation, Biomedical imaging, Bladder, Computer science, Image segmentation, Level set, Medical treatment, Shape, Visualization, graph cut algorithm, graph cuts, graph theory, image segmentation, interactive segmentation, interactive systems, level sets, medical image processing, segmentation, semi-automatic segmentation, shape priors},
pages = {755--762 vol. 1}
}
Downloads: 0
{"_id":"MhbQmcSJhCPJBzFbL","bibbaseid":"freedman-zhang-interactivegraphcutbasedsegmentationwithshapepriors-2005","downloads":0,"creationDate":"2018-01-22T16:01:02.782Z","title":"Interactive graph cut based segmentation with shape priors","author_short":["Freedman, D.","Zhang, T."],"year":2005,"bibtype":"inproceedings","biburl":"https://api.zotero.org/groups/2196137/items?key=9sAVQ9xrV4yCcI9wtDczc9Dg&format=bibtex&limit=100","bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"Interactive graph cut based segmentation with shape priors","volume":"1","doi":"10.1109/CVPR.2005.191","abstract":"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.","booktitle":"2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)","author":[{"propositions":[],"lastnames":["Freedman"],"firstnames":["D."],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Tao"],"suffixes":[]}],"month":"June","year":"2005","keywords":"Application software, Biomedical applications of radiation, Biomedical imaging, Bladder, Computer science, Image segmentation, Level set, Medical treatment, Shape, Visualization, graph cut algorithm, graph cuts, graph theory, image segmentation, interactive segmentation, interactive systems, level sets, medical image processing, segmentation, semi-automatic segmentation, shape priors","pages":"755–762 vol. 1","bibtex":"@inproceedings{freedman_interactive_2005,\n\ttitle = {Interactive graph cut based segmentation with shape priors},\n\tvolume = {1},\n\tdoi = {10.1109/CVPR.2005.191},\n\tabstract = {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.},\n\tbooktitle = {2005 {IEEE} {Computer} {Society} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR}'05)},\n\tauthor = {Freedman, D. and Zhang, Tao},\n\tmonth = jun,\n\tyear = {2005},\n\tkeywords = {Application software, Biomedical applications of radiation, Biomedical imaging, Bladder, Computer science, Image segmentation, Level set, Medical treatment, Shape, Visualization, graph cut algorithm, graph cuts, graph theory, image segmentation, interactive segmentation, interactive systems, level sets, medical image processing, segmentation, semi-automatic segmentation, shape priors},\n\tpages = {755--762 vol. 1}\n}\n\n","author_short":["Freedman, D.","Zhang, T."],"key":"freedman_interactive_2005","id":"freedman_interactive_2005","bibbaseid":"freedman-zhang-interactivegraphcutbasedsegmentationwithshapepriors-2005","role":"author","urls":{},"keyword":["Application software","Biomedical applications of radiation","Biomedical imaging","Bladder","Computer science","Image segmentation","Level set","Medical treatment","Shape","Visualization","graph cut algorithm","graph cuts","graph theory","image segmentation","interactive segmentation","interactive systems","level sets","medical image processing","segmentation","semi-automatic segmentation","shape priors"],"downloads":0,"html":""},"search_terms":["interactive","graph","cut","based","segmentation","shape","priors","freedman","zhang"],"keywords":["application software","biomedical applications of radiation","biomedical imaging","bladder","computer science","image segmentation","level set","medical treatment","shape","visualization","graph cut algorithm","graph cuts","graph theory","image segmentation","interactive segmentation","interactive systems","level sets","medical image processing","segmentation","semi-automatic segmentation","shape priors"],"authorIDs":[],"dataSources":["M8pbA37dQECNJ7i5D"]}