DocumentCode :
3442418
Title :
Integrating automatic and interactive brain tumor segmentation
Author :
Dam, Erik ; Loog, Marco ; Letteboer, Marloes
Author_Institution :
Image Anal. Group, IT Univ. of Copenhagen, Denmark
Volume :
3
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
790
Abstract :
This paper integrates automatic segmentation based on supervised learning with an interactive multi-scale watershed segmentation method. The combined method automatically provides an initial segmentation that applies the building blocks that the user can use in the interactive method. Thereby the two approaches are seamlessly integrated and the combined method can be used on the full range of problems from very easy to very difficult segmentation tasks resulting in different levels of interaction needed. The method is evaluated for the segmentation of brain tumors.
Keywords :
brain; image classification; image segmentation; learning (artificial intelligence); medical image processing; tumours; automatic segmentation method; image classification; interactive brain tumor segmentation; interactive multiscale watershed segmentation; supervised learning; Biomedical imaging; Brain modeling; Image analysis; Image segmentation; Joining processes; Lesions; Neoplasms; Pattern classification; Shape; Supervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334647
Filename :
1334647
Link To Document :
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