Title :
Modified fuzzy c-means clustering for automatic tongue base tumour extraction from MRI data
Author :
Doshi, Trushali ; Soraghan, John ; Grose, Derek ; MacKenzie, Kenneth ; Petropoulakis, Lykourgos
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. of Strathclyde, Glasgow, UK
Abstract :
Magnetic resonance imaging (MRI) is a widely used imaging modality to extract tumour regions to assist in radiotherapy and surgery planning. Extraction of a tongue base tumour from MRI is challenging due to variability in its shape, size, intensities and fuzzy boundaries. This paper presents a new automatic algorithm that is shown to be able to extract tongue base tumour from gadolinium-enhanced T1-weighted (T1+Gd) MRI slices. In this algorithm, knowledge of tumour location is added to the objective function of standard fuzzy c-means (FCM) to extract the tumour region. Experimental results on 9 real MRI slices demonstrate that there is good agreement between manual and automatic extraction results with dice similarity coefficient (DSC) of 0.77±0.08.
Keywords :
biological organs; biomedical MRI; medical image processing; pattern clustering; radiation therapy; tumours; MRI data; T1-Gd MRI slices; automatic tongue base tumour extraction; dice similarity coefficient; fuzzy boundaries; gadolinium-enhanced T1-weighted MRI slices; imaging modality; magnetic resonance imaging; modified fuzzy C-means clustering; radiotherapy; standard fuzzy c-means function; surgery planning; tumour location; Clustering algorithms; Image segmentation; Magnetic resonance imaging; Manuals; Standards; Tongue; Tumors; Hessian analysis; MRI; automatic tumour extraction; fuzzy c-means; throat detection;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon