@inproceedings{8651885a0c1e4f73a73f43ddc251bb8f,
title = "A Comparative Study of Meningioma Tumors Segmentation Methods from MR Images",
abstract = "Brain tumor segmentation from magnetic resonance (MR) images can have a great impact on improving diagnostics, growth rate prediction, and treatment planning. In this paper, we provide a comparative study of four well-known segmentation algorithms, namely k-means clustering, histogram thresholding (Otsu), fuzzy c-means thresholding, and region growing. For the region growing algorithm, the seed selection process is automated and enhanced by preprocessing the images and approximating the tumor regions using initial clustering and/or thresholding approaches. The evaluation and comparison of the algorithms is conducted using a data-set of T1-Weighted Contrast-Enhanced magnetic resonance imaging (MRI) brain images. Ground truth tumor images were provided by three experienced radiologists and are used in the evaluation process. Results showed that the enhanced region growing method had the highest mean dice similarity coefficient with a score of 0.87, and the lowest under-segmentation rate (17.46%). The fuzzy c-means thresholding method had the lowest over-segmentation rate (0.03%). This study serves as a baseline for other advanced tumor segmentation studies such as the ones using the emergent machine learning approaches.",
keywords = "Fuzzy C-Means thresholding, Histogram thresholding (Otsu), Image segmentation, K-Means clustering, Meningioma, MRI, Region growing",
author = "Mohanad Alkhodari and Omnia Hassanin and Salam Dhou",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 3rd International Conference on Signal Processing and Information Security, ICSPIS 2020 ; Conference date: 25-11-2020 Through 26-11-2020",
year = "2020",
month = nov,
day = "25",
doi = "10.1109/ICSPIS51252.2020.9340134",
language = "British English",
series = "2020 3rd International Conference on Signal Processing and Information Security, ICSPIS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 3rd International Conference on Signal Processing and Information Security, ICSPIS 2020",
address = "United States",
}