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MR Image Segmentation Based on Modified Ant Colony Algorithm

机译:基于改进蚁群算法的MR图像分割

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Magnetic resonance imaging (MRI) is a widely used method to obtain high quality medical image of the brain. Post-processing MR images with segmentation algorithms enhances the visualization and measurement of soft tissues and lesions. However, the conventional algorithms are not perfect and there are still some regions which are not partitioned accurately. In this paper, a new ant colony algorithm is presented in accordance with the defect of previous variety and stagnation. The contrast experimental results show that the new algorithm is not only of higher segmentation quality but also of higher computational speed, and prove that the algorithm is efficient and superior.
机译:磁共振成像(MRI)是一种获得大脑高质量医学图像的广泛使用的方法。使用分割算法对MR图像进行后处理可增强软组织和病变的可视化和测量。然而,常规算法并不完美,并且仍然存在一些区域没有被精确地划分。针对先前变种和停滞的缺陷,提出了一种新的蚁群算法。对比实验结果表明,该算法不仅具有较高的分割质量,而且具有较高的计算速度,证明了该算法的有效性和优越性。

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