Improved and robust detection of cell nuclei from four dimensional fluorescence images.
Improved and robust detection of cell nuclei from four dimensional fluorescence images.
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DOI：
10.1371/journal.pone.0101891
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Kobayashi TJ
中科院分区：
文献类型：
--
作者：
Bashar MK;Yamagata K;Kobayashi TJ
无分割的直接方法对于从高维图像中自动提取细胞核是非常有效的。确实存在一些这样的方法，但它们中的大多数不能确保算法对参数和噪声变化的鲁棒性。在这项研究中，我们提出了一种基于多尺度自适应滤波的方法，用于从四维（4D）荧光图像中有效和鲁棒地检测细胞核质心。在典型的直接方法的增强和初始检测步骤之间采用时间反馈机制。我们估计最小和最大的核直径从前一帧和反馈他们作为过滤器长度的多尺度增强的当前帧。在初始质心位置优化径向强度梯度函数以估计所有核直径。该过程继续以处理序列中的后续图像。因此，上述机制通过自动估计主要参数来确保适当的增强。这带来了鲁棒性，并保护系统免受加性噪声和错误参数的影响。之后，该方法及其单尺度变体被简化以进一步减少参数。该方法扩展到细胞核体积分割。同样的优化技术被应用到最终的增强图像的质心位置和估计的直径投影到二进制候选区域分割nucleusvolumes. We的方法最后集成了一个简单的顺序跟踪方法，以建立在4D空间中的核轨迹。实验评估与五个图像序列（每个具有271个3D序列图像）对应于五个不同的小鼠胚胎显示有前途的性能，我们的方法在核检测，分割和跟踪。对101幅胚胎三维图像的子序列进行了详细的分析，结果表明，与使用不合适的大值参数的先前方法相比，所提出的方法可以将细胞核检测精度提高9倍。结果还证实，所提出的方法及其变体实现高检测精度（98平均F-措施），而不管滤波器参数和噪声水平的大的变化。
Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9 over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies ( 98 mean F-measure) irrespective of the large variations of filter parameters and noise levels.
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影响因子：
3.7
作者：
Bashar MK;Komatsu K;Fujimori T;Kobayashi TJ
通讯作者：
Kobayashi TJ
影响因子：
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作者：
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生物图像信息学：工程生物学的新领域。
影响因子：
5.8
作者：
Peng, Hanchuan
通讯作者：
Peng, Hanchuan