IEEE J Biomed Health Inform. 2015 Mar;19(2):687-97. doi: 10.1109/JBHI.2014.2312293.
Ca(2+) plays an important role in the regulation of cellular functions. Local calcium events, e.g., calcium sparks, not only bring insights into Ca(2+) signaling but also contribute to the understanding of various cellular processes. However, it is challenging to detect calcium sparks, due to their transient properties and high level of nonstationary noises in microscopic images. Most of existing algorithms tend to have limitations for the detection of calcium sparks, e.g., empirically defined hard thresholds or poor applicability to nonstationary conditions. This paper presents a novel two-phase greedy pursuit (TPGP) algorithm for automatic detection and characterization of calcium sparks. In Phase I, a coarse-grained search is conducted across the whole image to identify the predominant sparks. In Phase II, adaptive basis function model is developed for the fine-grained representation of detected sparks. It may be noted that the proposed TPGP algorithms overcome the drawback of hard thresholding in most of previous approaches. Furthermore, the morphology of detected sparks is effectively modeled with multiscale basis functions in Phase II, thereby facilitating the analysis of physiological features. We evaluated and validated the TPGP algorithms using both real-word and synthetic images with multiple noise levels and varying baselines. Experimental results show that TPGP algorithms yield better performances than previous hard-thresholding approaches in terms of both sensitivities and positive predicted values. The present research provides the community a robust tool for the automatic detection and characterization of transient calcium signaling.
钙离子在细胞功能调节中起着重要作用。局部钙事件，如钙火花，不仅为钙信号提供了深入的了解，也有助于理解各种细胞过程。然而，由于其瞬态特性和微观图像中高水平的非平稳噪声，检测钙火花具有挑战性。现有的大多数算法在检测钙火花方面都存在局限性，例如经验定义的硬阈值或对非平稳条件的适用性差。本文提出了一种新颖的两阶段贪婪追踪（TPGP）算法，用于自动检测和表征钙火花。在第一阶段，对整个图像进行粗粒度搜索，以识别主要的火花。在第二阶段，为检测到的火花开发了自适应基函数模型进行细粒度表示。需要注意的是，与大多数先前的方法相比，所提出的 TPGP 算法克服了硬阈值的缺点。此外，在第二阶段，使用多尺度基函数有效地对检测到的火花的形态进行建模，从而有助于分析生理特征。我们使用具有多种噪声水平和不同基线的真实和合成图像对 TPGP 算法进行了评估和验证。实验结果表明，TPGP 算法在灵敏度和阳性预测值方面均优于先前的硬阈值方法。本研究为自动检测和表征瞬态钙信号提供了一种强大的工具。
