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基于GFO和标记点分水岭算法的医学图像分割
利用基于广义模糊算子 GFO 的边缘检测算法来改进标记点分水岭分割 很有用-GFO and marking points on the watershed algorithm for medical image segmentation based on generalized fuzzy operator GFO edge detection algorithm to improve the marking point of the waters
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用于快速图像分割，此算法能使图像根据自身的灰度值自动分割。 -For fast image segmentation.This algorithm makes the image gray value according to their segmentation.
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在为分割使用分水岭变换之前，通常使用梯度幅度来预处理图像。-Before using watershed transformation for segmentation,we usually use gradient magnitude to preprocessing the image.
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改进分水岭方法定位虹膜，采用形态学开闭重建运算对图像进行滤波，进行前后景标记，从而进行分割图像-Improved watershed method to locate the iris, using morphological opening and closing operation for image reconstruction filter, before and after King Mark, thereby performing image segmentation
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图像分割是一种重要的图像分析技术，对图像分割的研究一直是图像技术研究中的热点和焦点。分水岭算法是基于数学形态学理论的图像分割算法，但是对噪声敏感且存在过分割的现象。为提高图像分割效果，本文通过对影像进行滤波处理，用改进的快速区域合并算法优化分水岭算法进行影像分割。实验结果与MeanShift算法得到的结果对比，证明此算法可以获得较好的分割效果。-In recent years, the watershed line has emerged as the primary tool of mathe
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Semi-automatic watershed medical image segmentation methods
for customized cancer radiation treatment planning simulation
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we present a segmentation algorithm for color
images that uses the watershed algorithm to segment either the twodimensional
(2-D) or the three-dimensional (3-D) color histogram of
an image.
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