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Brain tumor CT image segmentation based on SLIC0 superpixels

机译:基于SLIC0超像素的脑肿瘤CT图像分割

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摘要

The brain tumor CT image segmentation frequently suffers from the fuzzy edges, and manual segmentation mainly relies on doctor's clinical experience. For the purpose to accurately segment brain tumor, a method for brain tumor CT image segmentation based on SLIC0 superpixels is proposed. Firstly, the simple linear iterative clustering version with 0 (SLIC0) is employed to generate superpixels; Secondly, region merging is adopted to merge the similar superpixels according to their gray, and finally segment the brain tumor regions. Experiments show that this method can accurately segment the target tumor, and segmentation accuracy can be adjusted by setting the pixel number of superpixels.
机译:脑肿瘤CT图像分割经常遭受模糊边缘,手动分割主要依赖于医生的临床经验。为了准确地分段脑肿瘤,提出了一种基于SLIC0超像素的脑肿瘤CT图像分割方法。首先,采用具有0(SLIC0)的简单线性迭代群集版本来生成超像素;其次,采用区域合并以根据其灰色合并类似的超像素,最后段细分脑肿瘤区域。实验表明,该方法可以准确地分段靶肿瘤,并且可以通过设置超像素的像素数来调整分割精度。

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