Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 1 1 2014 03 30 48 53 EN Anahita Fathi-Kazerooni Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Iran AND Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Iran. Meysam Mohseni Neurosurgery Ward, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran. Hamid Reza Saligheh-Rad Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Iran AND Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced MedicalTechnologies, Iran. 2015 10 13 2015 10 13 Purpose: Glioblastoma Multiforme (GBM) brain tumor is heterogeneous in nature; so, its quantification depends on how to accurately segment different parts of the tumor, i.e. active tumor, edema and necrosis. This procedure becomes more effective when physiological information like diffusion-weighted-imaging (DWI) and perfusion-weighted-imaging (PWI) are incorporated with the anatomical MRI. In this preliminary tumor quantification work, the idea is to characterize different regions of the GBM tumors in an MRI-based multi-parametric approach to achieve more accurate characterization of pathological regions, which cannot be obtained by using individual modalities. Methods: For this purpose, three MR sequences, namely T2-weighted imaging (anatomical MR imaging), PWI and DWI of five GBM patients were acquired. To enhance the delineation of the boundaries of each pathological region (peri-tumoral edema, tumor and necrosis), the spatial fuzzy C-means (FCM) algorithm is combined with the region growing (RG) method. Results: The results show that exploiting the multi-parametric approach along with the proposed segmentation method can improve characterization of tumor cells, edema and necrosis in comparison to mono-parametric imaging approach. Conclusion: The proposed MRI-based multi-parametric segmentation approach has the potential to accurately segment tumorous regions, leading to an efficient design of the treatment planning, e.g. in radiotherapy. https://fbt.tums.ac.ir/index.php/fbt/article/view/16 https://fbt.tums.ac.ir/index.php/fbt/article/download/16/15