Signal and Noise Modeling in Confocal Laser Scanning Fluorescence Microscopy

Signal and Noise Modeling in Confocal Laser Scanning Fluorescence Microscopy
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共焦激光扫描荧光显微镜中的信号和噪声建模

DOI:
10.1007/978-3-642-33415-3_47
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发表时间:
2012
期刊:
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
影响因子:
--
通讯作者:
Til Aach
Til Aach
中科院分区:
--
文献类型:
--
作者:
Gerlind Herberich;Reinhard Windoffer;Rudolf E. Leube;Til Aach

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荧光共聚焦激光扫描显微镜(CLSM)通过在活细胞中采集荧光标记蛋白质的3D时间序列,彻底改变了生物医学研究中亚细胞结构的成像,从而形成了自动定量其形态和动态特征的基础。由于固有的弱荧光,CLSM图像表现出低SNR。我们提出了一种新的模型,在CLSM中的信号和噪声的传输,这是理论上的声音,以及通过测量的3D噪声功率谱,信号依赖性和分布的像素强度统计的严格分析证实。我们的模型比以前提出的模型提供了更好的拟合数据。此外,它形成了基础(i)的CLSM成像过程的模拟必不可少的CLSM图像分析算法的定量评估,(ii)的泊松去噪算法的应用和(iii)的荧光信号的重建。
Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.
用于细胞病理学癌症诊断的高动态范围显微镜
DOI: --
发表时间: 2009
期刊: IEEE Journal on Selected Topics in Signal Processing
影响因子: --
作者:
A. Bell;J. Brauers;J. Kaftan;D. Meyer;A. Böcking;T. Aach
通讯作者: T. Aach
图像传感器噪声的泊松近似
DOI: --
发表时间: 2010
期刊:
影响因子: --
作者:
Xiaodan Jin
通讯作者: Xiaodan Jin