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Article

3D-MRI Brain Tumor Detection Model Using Modified Version of Level Set Segmentation Based on Dragonfly Algorithm

1
Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt
2
Department of Information Technology, Institute of Graduate Studies and Research, Alexandria University, Alexandria 21526, Egypt
3
Faculty of Science, Department of Mathematics, Damanhour University, Damanhour 22511, Egypt
*
Author to whom correspondence should be addressed.
Symmetry 2020, 12(8), 1256; https://doi.org/10.3390/sym12081256
Received: 28 June 2020 / Revised: 20 July 2020 / Accepted: 25 July 2020 / Published: 29 July 2020
(This article belongs to the Special Issue Symmetry in Vision Ⅱ)
Accurate brain tumor segmentation from 3D Magnetic Resonance Imaging (3D-MRI) is an important method for obtaining information required for diagnosis and disease therapy planning. Variation in the brain tumor’s size, structure, and form is one of the main challenges in tumor segmentation, and selecting the initial contour plays a significant role in reducing the segmentation error and the number of iterations in the level set method. To overcome this issue, this paper suggests a two-step dragonfly algorithm (DA) clustering technique to extract initial contour points accurately. The brain is extracted from the head in the preprocessing step, then tumor edges are extracted using the two-step DA, and these extracted edges are used as an initial contour for the MRI sequence. Lastly, the tumor region is extracted from all volume slices using a level set segmentation method. The results of applying the proposed technique on 3D-MRI images from the multimodal brain tumor segmentation challenge (BRATS) 2017 dataset show that the proposed method for brain tumor segmentation is comparable to the state-of-the-art methods. View Full-Text
Keywords: 3D-MRI tumor detection; bio-inspired clustering; level set segmentation 3D-MRI tumor detection; bio-inspired clustering; level set segmentation
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MDPI and ACS Style

Khalil, H.A.; Darwish, S.; Ibrahim, Y.M.; Hassan, O.F. 3D-MRI Brain Tumor Detection Model Using Modified Version of Level Set Segmentation Based on Dragonfly Algorithm. Symmetry 2020, 12, 1256. https://doi.org/10.3390/sym12081256

AMA Style

Khalil HA, Darwish S, Ibrahim YM, Hassan OF. 3D-MRI Brain Tumor Detection Model Using Modified Version of Level Set Segmentation Based on Dragonfly Algorithm. Symmetry. 2020; 12(8):1256. https://doi.org/10.3390/sym12081256

Chicago/Turabian Style

Khalil, Hassan A.; Darwish, Saad; Ibrahim, Yasmine M.; Hassan, Osama F. 2020. "3D-MRI Brain Tumor Detection Model Using Modified Version of Level Set Segmentation Based on Dragonfly Algorithm" Symmetry 12, no. 8: 1256. https://doi.org/10.3390/sym12081256

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