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Segmentation of Brain MRI Image with GVF Snake Model

机译:用GVF蛇模型进行脑MRI图像的分割

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摘要

Medical image segmentation is the foundation and research focus in the medical image processing field. In this paper the normalized GVF Snake model combines with traditional edge detection is proposed for the brain MRI image semiautomatic segmentation. The thinning Canny result is used to calculate the edge map gradient of the GVF snake model. Then the normalized GVF snake model deforms with the manual initial contour. Simulation results show that this method can extract the boundary of the tumor accurately, and the method can overcome the problem that traditional GVF snake cannot efficient converge to the weak boundary. The method has positive significance in practical applications.
机译:医学图像分割是医学图像处理领域的基础和研究重点。本文提出了具有传统边缘检测的标准化GVF蛇模型,用于脑MRI图像半自动分割。稀疏的罐头结果用于计算GVF蛇模型的边缘映射梯度。然后,标准化的GVF蛇模型与手动初始轮廓变形。仿真结果表明,该方法可以准确地提取肿瘤的边界,并且该方法可以克服传统GVF蛇无法有效地收敛到弱边界的问题。该方法对实际应用具有积极意义。

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