Abstract
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.
Highlights
The American national brain tumor society noted that approximately 700,000 humans suffered from brain tumors in 2017 [1]
In order to overcome the drawbacks of drawbacks of existing brain tumor segmentation systems, the work presented in this paper aimed to existing brain tumor segmentation systems, the work presented in this paper aimed to provide an provide an efficient model that combines two-step dragonfly algorithm-based clustering and the level set method for segmenting 3D Magnetic Resonance Imaging (3D-Magnetic Resonance Imaging (MRI)) scans
This paper offers a modified bio-inspired level set segmentation technique to extract brain tumors in MRI images
Summary
The American national brain tumor society noted that approximately 700,000 humans suffered from brain tumors in 2017 [1]. A brain tumor is an abandoned growth of cancerous cells inside or around the brain. These tumors are classified into two main types, i.e., benign (noncancerous) and malignant (cancerous) [2]. Knowing the tumor type can, help to understand the patient’s condition. The early detection and accurate recognition of brain tumors are vital. A timely diagnosis helps in the treatment procedure
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