Background: In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images. This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain.
Hsieh et al. REF uses fuzzy c-means (FCM) and region growing algorithms for automatic tumor image segmentation in meningioma patients.
Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing
BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making
Medicine Computer Science