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公开(公告)号：US20120093376A1
公开(公告)日：2012-04-19
申请号：US12904627
申请日：2010-10-14
CPC分类号： G06K9/0014 , G06K9/0051
摘要： The present invention relates to systems and methods for reducing noise in image data. Preferred embodiments relate to methods for analyzing two-photon in vivo imaging of biological systems. With neuronal population imaging with subcellular resolution, this modality offers an approach for gaining a fundamental understanding of brain anatomy and physiology. Analysis of calcium imaging data requires denoising, that is separating the signal from complex physiological noise. To analyze two-photon brain imaging data, for example, harmonic regression plus colored noise model and an efficient cyclic descent algorithm for parameter estimation. This approach reliably separates stimulus-evoked fluorescence response from background activity and noise, assesses goodness of fit, and estimates confidence intervals and signal-to-noise ratio.
摘要翻译： 本发明涉及降低图像数据噪声的系统和方法。 优选实施方案涉及用于分析生物系统的双光子体内成像的方法。 对于具有亚细胞分辨率的神经元群体成像，该模式提供了一种获得对脑解剖学和生理学的基础理解的方法。 钙成像数据的分析需要去噪，即将信号与复杂的生理噪声分离。 分析双光子脑成像数据，例如，谐波回归加彩色噪声模型和有效的循环下降算法进行参数估计。 这种方法将刺激诱发荧光响应与背景活动和噪声可靠地分离，评估拟合优度，并估计置信区间和信噪比。
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公开(公告)号：US08903192B2
公开(公告)日：2014-12-02
申请号：US12904627
申请日：2010-10-14
CPC分类号： G06K9/0014 , G06K9/0051
摘要： The present invention relates to systems and methods for reducing noise in image data. Preferred embodiments relate to methods for analyzing two-photon in vivo imaging of biological systems. With neuronal population imaging with subcellular resolution, this modality offers an approach for gaining a fundamental understanding of brain anatomy and physiology. Analysis of calcium imaging data requires denoising, that is separating the signal from complex physiological noise. To analyze two-photon brain imaging data, for example, harmonic regression plus colored noise model and an efficient cyclic descent algorithm for parameter estimation. This approach reliably separates stimulus-evoked fluorescence response from background activity and noise, assesses goodness of fit, and estimates confidence intervals and signal-to-noise ratio.
摘要翻译： 本发明涉及降低图像数据噪声的系统和方法。 优选实施方案涉及用于分析生物系统的双光子体内成像的方法。 对于具有亚细胞分辨率的神经元群体成像，该模式提供了一种获得对脑解剖学和生理学的基础理解的方法。 钙成像数据的分析需要去噪，即将信号与复杂的生理噪声分离。 分析双光子脑成像数据，例如，谐波回归加彩色噪声模型和有效的循环下降算法进行参数估计。 这种方法将刺激诱发的荧光响应与背景活动和噪声可靠地分离，评估拟合优度，并估计置信区间和信噪比。
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