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Cell image segmentation using binary threshold and greyscale image processing
Cell image segmentation using binary threshold and greyscale image processing
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机译：使用二进制阈值和灰度图像处理的细胞图像分割
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摘要
An image segmentation method comprises: thresholding a greyscale image of plural nuclei to create a black and white image; post processing the B/W image to remove objects failing to meet criteria based on the B/W image and greyscale image (e.g. calculating the gradient in the greyscale image at boundaries identified in the B/W image and comparing this with a gradient threshold); segmenting to extract objects corresponding to objects remaining after this processing; and further using edge detection on the segmented image, to determine edges of real nuclei. Objects with areas less than a predetermined number of pixels may be removed. Grey scale images may be smoothed via Gaussian filtering, and convolved with the derivative of a Gaussian, prior to gradient calculation. A Canny edge detector and gradient vector flow snake may be used for edge detection. The invention relates to optimizing the initialization and convergence of active contours (or 'snakes') for segmentation of cell nuclei into objects and holes in histological sections.
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