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New Region Growing Segmentation Technique for MR Images with Weak Boundaries

机译:具有弱边界的MR图像区域增长分割新技术

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In medical image processing, segmented images are used for studying anatomical structures, diagnosis and assisting in surgical planning. Our goal is to segment 2D/3D MR images which contain weak boundaries between different tissues. Region growing method cannot specifically segment the tissues with weak boundaries because pixels inside the region and outside have similar intensity. We introduce a new automatic threshold method for region growing. The pixels around boundaries have lower probability of intensities than the pixels inside and outside the tissues. Then, the automatic threshold for region growing will be computed as a function of pixel intensity value and probability of intensities. The experimental results show that the proposed technique produces accurate and stable results.
机译:在医学图像处理中,分割后的图像用于研究解剖结构,诊断和辅助手术计划。我们的目标是分割2D / 3D MR图像,该图像包含不同组织之间的弱边界。区域生长方法无法专门分割边界较弱的组织,因为该区域内部和外部的像素具有相似的强度。我们为区域增长引入了一种新的自动阈值方法。与组织内部和外部的像素相比,边界周围的像素具有较低的强度概率。然后,将根据像素强度值和强度概率来计算区域增长的自动阈值。实验结果表明,所提出的技术产生了准确,稳定的结果。

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