Title :
An interactive graph cut method for brain tumor segmentation
Author :
Birkbeck, Neil ; Cobzas, Dana ; Jagersand, Martin ; Murtha, Albert ; Kesztyues, Tibor
Author_Institution :
Univ. of Alberta, Edmonton, AB, Canada
Abstract :
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue among different patients and, in many cases, similarity between tumor and normal tissue. We propose a semi-automatic interactive brain tumor segmentation system that incorporates 2D interactive and 3D automatic tools with the ability to adjust operator control. The provided methods are based on an energy that incorporates region statistics computed on available MRI modalities and the usual regularization term. The energy is efficiently minimized on-line using graph cut. Experiments with radiation oncologists testing the semi-automatic tool vs. a manual tool show that the proposed system improves both segmentation time and repeatability.
Keywords :
biomedical MRI; brain; graph theory; image segmentation; interactive systems; tumours; 2D interactive tool; 3D automatic tool; MRI data; brain tumor segmentation; interactive graph cut method; operator control; radiation oncologists testing; semi-automatic interactive brain tumor segmentation system; tumor tissue; Automatic control; Biomedical imaging; Cancer; Control systems; Image segmentation; Labeling; Magnetic resonance imaging; Neoplasms; Statistics; Testing;
Conference_Titel :
Applications of Computer Vision (WACV), 2009 Workshop on
Conference_Location :
Snowbird, UT
Print_ISBN :
978-1-4244-5497-6
DOI :
10.1109/WACV.2009.5403049