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首页> 外文期刊>Journal of Imaging Science and Technology >Region Growing Segmentation of Chromatin Clumps of Ovarian Cells Using Adaptive Gradients
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Region Growing Segmentation of Chromatin Clumps of Ovarian Cells Using Adaptive Gradients

机译：使用自适应梯度的卵巢细胞染色质团生长区域分割

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摘要

An iterative region growing algorithm for segmentation within the chromatin of ovarian cells is presented. The growing procedure starts with small seed regions that are relatively easier to segment accurately by an intensity thresholding process. In each of the iterations, the growth decision is made based on whether a given test is passed. The growth test is set to pass more easily in the first iterations when the intensities are low and the gradients are high. As the region grows, the test gradually becomes more difficult to pass. The growth stops when it reaches the boundaries where the pixel intensities are high and the gradients decrease to zero. To reduce the noise effects that may interrupt the region growth, a preprocessing median filter is applied to smooth the original image and suppress the image noise. Results are demonstrated on ovarian cells.
机译：提出了一种用于卵巢细胞染色质内分割的迭代区域增长算法。生长过程从较小的种子区域开始，该区域相对较小，通过强度阈值处理可以更准确地进行分割。在每个迭代中，根据是否通过给定的测试来做出增长决定。当强度低且梯度高时，生长测试将在第一次迭代中更容易通过。随着区域的增长，测试逐渐变得越来越难以通过。当它到达像素强度高且渐变降低到零的边界时，增长停止。为了减少可能中断区域增长的噪声影响，可以应用预处理中值滤波器来平滑原始图像并抑制图像噪声。结果显示在卵巢细胞上。

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