Improved segmentation of meristem cells by an automated optimisation algorithm
Improved segmentation of meristem cells by an automated optimisation algorithm
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通过自动优化算法改进分生组织细胞的分割
DOI：
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发表时间：
2017
期刊：
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通讯作者：
James A. H. Murray
中科院分区：
文献类型：
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作者：
O. Rojas;M. Forero;J. M. Menéndez;Angharad Jones;W. Dewitte;James A. H. Murray
提出了一种基于数学形态学的显微图像分生组织细胞自动分割新方法。分生组织是一种植物组织，它产生了所有的结构。在共聚焦显微镜下，分生组织细胞被明亮的细胞所包围。图像的特点是非常低的对比度和绝对损失的边缘时，更深入分生组织的区域。边缘模糊，不连续，有时无法区分，并且细胞内的强度水平与图像的背景相似。分割的最佳参数是通过称为参数分割调整（PST）的迭代过程找到的。它比较在连续步骤中获得的分割图像，使用优化函数来确定哪一对允许获得最佳分割。该技术进行了验证，比较地面实况图像与输出分割图像，以验证最佳参数是否接近所提出的技术。接收器操作特性（ROC）分析用于验证参数变化的趋势，朝向分割图像和地面实况图像之间的最大相似性点。其他相似性指数也产生了相同的结果。
This paper presents a new technique based on mathematical morphology for the automatic segmentation of meristem cells in microscopy images. The meristem is a plant tissue that gives rise to all its structures. Meristem cells in confocal microscopy are seen as dark areas surrounded by bright ones. Images are characterised by regions of very low contrast and absolute loss of edges when deeper into the meristem. Edges are blurred, discontinuous, sometimes indistinguishable, and the intensity level inside the cells is similar to the background of the image. The optimal parameters for the segmentation are found by means of an iterative process called the Parametric Segmentation Tuning (PST). It compares the segmented images, obtained in successive steps, using an optimisation function to determine which pair allows to get the best segmentation. The technique was validated comparing a ground truth image with the output segmentation image to verify if the optimal parameters are close to those found with the proposed technique. A Receiver Operating Characteristic (ROC) analysis is used to verify the trend of the parameter variation towards the point of maximum similarity between the segmented and the ground truth images. Other similarity indexes were found to produce the same results.