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