Picture of neon light reading 'Open'

Discover open research at Strathprints as part of International Open Access Week!

23-29 October 2017 is International Open Access Week. The Strathprints institutional repository is a digital archive of Open Access research outputs, all produced by University of Strathclyde researchers.

Explore recent world leading Open Access research content this Open Access Week from across Strathclyde's many research active faculties: Engineering, Science, Humanities, Arts & Social Sciences and Strathclyde Business School.

Explore all Strathclyde Open Access research outputs...

Semi-automatic segmentation of tongue tumors from magnetic resonance imaging

Doshi, Trushali and Soraghan, John and Petropoulakis, Lykourgos and Gross, Derek and MacKenzie, Kenneth (2013) Semi-automatic segmentation of tongue tumors from magnetic resonance imaging. In: 2013 20th International Conference on Systems, Signals and Image Processing (IWSSIP). IEEE, pp. 143-146. ISBN 9781479909414

Full text not available in this repository. Request a copy from the Strathclyde author


Radiation therapy is one of the most effective modalities for treatment of tongue cancer. In order to optimize radiation dose to the tumor region, it is necessary to segment the tumor from normal region. This paper presents a new semiautomatic algorithm that is demonstrated to be able to segment tongue tumor from gadolinium-enhanced T1-weighted magnetic resonance imaging (MRI) to support radiation planning. This algorithm takes sequential MRI slices with visible tongue tumor. The Tumor's region from each slice is segmented using three steps (i) preprocessing, (ii) initialization and (iii) localized region-based level set segmentation. The segmentation results obtained from proposed algorithm are compared with manual segmentation from clinical expert. Results from 9 MRI slices show that there is a good overlap between semi-automatic and manual segmentation results with dice similarity coefficient (DSC) of 0.87±0.05.