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A hybrid method for automatic skull stripping of magnetic resonance images (MRI) of human head scans

机译:用于人头扫描的磁共振图像(MRI)自动颅骨剥离的混合方法

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Automatic segmentation of brain tissue on magnetic resonance images is a challenging process due to the variation in brain shapes and similarity of intensity values in the brain and non-brain tissues. Skull stripping is a process of segmenting brain and non-brain tissues in MR brain images. It is an important image processing step in many neuroimage studies. In this paper, we propose a new skull stripping method for magnetic resonance image (MRI) of human head scans based on image contour. We used hybrid method, which combines two or more methods to produce better result. This algorithm first pre-processes the image by denoising using mean filter. The denoised image is blurred to obtain a rough brain mask using image contour. The rough mask is further processed to produce final brain mask. The proposed algorithm is compared with standard manual stripping (Gold standard) images and produced significant result. The experimental results show that the proposed method extracted the brain accurately which are comparable to that of BSE, BET, WAT and HWA using IBSR data set.
机译:由于大脑形状的变化以及大脑和非大脑组织中强度值的相似性,磁共振图像上脑组织的自动分割是一个具有挑战性的过程。颅骨剥离是在MR大脑图像中分割大脑和非大脑组织的过程。在许多神经图像研究中,它是重要的图像处理步骤。在本文中,我们提出了一种新的颅骨剥离方法,用于基于图像轮廓的人头扫描磁共振图像(MRI)。我们使用了混合方法,该方法结合了两种或更多种方法来产生更好的结果。该算法首先使用均值滤波器通过降噪对图像进行预处理。去噪的图像被模糊以使用图像轮廓获得粗糙的脑罩。进一步加工粗糙面罩以产生最终的脑罩。将所提出的算法与标准的手动剥离(金标准)图像进行比较,并得出了显着的结果。实验结果表明,该方法利用IBSR数据集可以准确地提取出与BSE,BET,WAT和HWA相当的大脑。

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