Curvelet initialized level set cell segmentation for touching cells in low contrast images
Curvelet initialized level set cell segmentation for touching cells in low contrast images
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DOI：
10.1016/j.compmedimag.2016.01.002
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发表时间：
2016-04-01
影响因子：
5.7
通讯作者：
Sahambi, J. S.
中科院分区：
文献类型：
--
作者：
Kaur, Sarabpreet;Sahambi, J. S.
细胞分割是细胞自动分析的重要组成部分。提出了一种在低对比度图像中提取接触细胞的细胞核和细胞边界的方法。首先，采用多尺度顶帽滤光片和h-Maxima相结合的方法提高低对比度细胞图像的对比度。在此基础上，提出了一种基于Curvelet的初始化水平集方法来检测细胞核和边界。图像增强结果用峰值信噪比进行了验证，分割结果用准确度、敏感度和精度指标进行了验证。结果表明，该方法提高了性能指标的取值。(C)2016爱思唯尔有限公司。保留所有权利。
Cell segmentation is an important element of automatic cell analysis. This paper proposes a method to extract the cell nuclei and the cell boundaries of touching cells in low contrast images. First, the contrast of the low contrast cell images is improved by a combination of multiscale top hat filter and h-maxima. Then, a curvelet initialized level set method has been proposed to detect the cell nuclei and the boundaries. The image enhancement results have been verified using PSNR (Peak Signal to noise ratio) and the segmentation results have been verified using accuracy, sensitivity and precision metrics. The results show improved values of the performance metrics with the proposed method. (C) 2016 Elsevier Ltd. All rights reserved.