Rapid 3-D delineation of cell nuclei for high-content screening platforms.
Rapid 3-D delineation of cell nuclei for high-content screening platforms.
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DOI：
10.1016/j.compbiomed.2015.04.025
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发表时间：
2016-02-01
影响因子：
7.7
通讯作者：
Knudsen, Beatrice S.
中科院分区：
文献类型：
--
作者：
Gertych, Arkadiusz;Ma, Zhaoxuan;Tajbakhsh, Jian;Velasquez-Vacca, Adriana;Knudsen, Beatrice S.
高分辨率三维（3-D）显微镜与荧光标记的多路复用相结合，允许大量细胞核的高内容分析。3D筛查平台的完全自动化需要图像处理算法，该算法可以在几乎没有人为干预的情况下准确且稳健地描绘图像中的细胞核。基于成像的高内涵筛选最初是作为药物发现的有力工具而开发的。然而，细胞融合、细胞核染色的复杂性以及细胞核与背景之间的对比度差导致缓慢且不可靠的3-D图像处理，因此对研究药物反应的性能产生负面影响。在这里，我们提出了一种新方法3D-RSD，通过3D径向对称性来描绘细胞核，并在药物治疗的人类癌细胞的高分辨率图像数据上进行测试。通过从2351个核（27个共聚焦堆栈）手动生成的地面实况来评估核检测性能。当与其他三种细胞核分割方法相比时，3D-RSD具有更好的真阳性率83.3%和F分数0.895+/-0.045（p值=0.047）。总之，3D-RSD是一种具有非常好的整体分割性能的方法。此外，径向对称的实现提供了良好的处理速度，并使3D-RSD对染色图案不太敏感。特别地，3D-RSG方法在细胞系中表现良好，这些细胞系通常用于基于成像的HCS平台，并且受到核拥挤和重叠的影响，这阻碍了特征提取。
High-resolution three-dimensional (3-D) microscopy combined with multiplexing of fluorescent labels allows high-content analysis of large numbers of cell nuclei. The full automation of 3-D screening platforms necessitates image processing algorithms that can accurately and robustly delineate nuclei in images with little to no human intervention. Imaging-based high-content screening was originally developed as a powerful tool for drug discovery. However, cell confluency, complexity of nuclear staining as well as poor contrast between nuclei and background result in slow and unreliable 3-D image processing and therefore negatively affect the performance of studying a drug response. Here, we propose a new method, 3D-RSD, to delineate nuclei by means of 3-D radial symmetries and test it on high-resolution image data of human cancer cells treated by drugs. The nuclei detection performance was evaluated by means of manually generated ground truth from 2351 nuclei (27 confocal stacks). When compared to three other nuclei segmentation methods, 3D-RSD possessed a better true positive rate of 83.3% and F-score of 0.895+/-0.045 (p- value=0.047). Altogether, 3D-RSD is a method with a very good overall segmentation performance. Furthermore, implementation of radial symmetries offers good processing speed, and makes 3D-RSD less sensitive to staining patterns. In particular the 3D-RSG method performs well in cell lines, which are often used in imaging-based HCS platforms and are afflicted by nuclear crowding and overlaps that hinder feature extraction.
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影响因子：
3.8
作者：
Brandhagen BN;Tieszen CR;Ulmer TM;Tracy MS;Goyeneche AA;Telleria CM
通讯作者：
Telleria CM
DOI：
10.1093/bioinformatics/btu080
发表时间：
2014-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Maška M;Ulman V;Svoboda D;Matula P;Matula P;Ederra C;Urbiola A;España T;Venkatesan S;Balak DM;Karas P;Bolcková T;Streitová M;Carthel C;Coraluppi S;Harder N;Rohr K;Magnusson KE;Jaldén J;Blau HM;Dzyubachyk O;Křížek P;Hagen GM;Pastor-Escuredo D;Jimenez-Carretero D;Ledesma-Carbayo MJ;Muñoz-Barrutia A;Meijering E;Kozubek M;Ortiz-de-Solorzano C
通讯作者：
Ortiz-de-Solorzano C
影响因子：
10.6
作者：
Chan, TF;Vese, LA
通讯作者：
Vese, LA
影响因子：
3
作者：
Bjornsson, Christopher S.;Lin, Gang;Roysam, Badrinath
通讯作者：
Roysam, Badrinath
影响因子：
3.7
作者：
Koyuncu CF;Arslan S;Durmaz I;Cetin-Atalay R;Gunduz-Demir C
通讯作者：
Gunduz-Demir C