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Segmentation Using a Region Growing Thresholding

机译:使用区域增长阈值进行分割

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Our research deals with a semi-automatic region-growing segmentation technique. This method only needs one seed inside the region of interest (ROI). We applied it for spinal cord segmentation but it also shows results for parotid glands or even tumors. Moreover, it seems to be a general segmentation method as it could be applied in other computer vision domains then medical imaging. We use both the thresholding simplicity and the spatial information. The gray-scale and spatial distances from the seed to all the other pixels are computed. By normalizing and subtracting to 1 we obtain the probability for a pixel to belong to the same region as the seed. We will explain the algorithm and show some preliminary results which are encouraging.
机译:我们的研究涉及一种半自动区域增长分割技术。此方法仅在目标区域(ROI)内需要一个种子。我们将其用于脊髓分割,但它也显示了腮腺甚至肿瘤的结果。而且,这似乎是一种通用的分割方法,因为它可以应用于除医学成像之外的其他计算机视觉领域。我们同时使用阈值简单性和空间信息。计算从种子到所有其他像素的灰度和空间距离。通过归一化并减去1,我们可以获得像素与种子属于同一区域的概率。我们将解释该算法并显示一些令人鼓舞的初步结果。

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