Colocalization analysis yields superior results after image restoration
Colocalization analysis yields superior results after image restoration
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DOI：
10.1002/jemt.20066
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发表时间：
2004-06-01
影响因子：
2.5
通讯作者：
Marbet, P
中科院分区：
文献类型：
--
作者：
Landmann, L;Marbet, P
共定位分析是一个强有力的工具，用于演示的空间和时间重叠的荧光探针分布模式。在未经处理的图像中，背景通过损害分辨率和模糊低强度范围内的图像细节来影响图像质量。由于共焦图像遭受高达30%最大强度的背景水平，共定位分析，这是一个典型的分割过程，是有限的高强度信号。此外，噪声引起的假阳性事件（“灰尘”）可能会扭曲结果。因此，背景抑制对于这种类型的图像分析至关重要。合成和生物对象的分析表明，中值滤波能够成功地消除噪声引起的共定位事件。其缺点包括偶尔产生假阳性和假阴性结果以及分辨率的固有损害。相反，通过去卷积的图像恢复将背景抑制到非常低的水平（
Colocalization analysis is a powerful tool for the demonstration of spatial and temporal overlap in the distribution patterns of fluorescent probes. In unprocessed images, background affects image quality by impairing resolution and obscuring image detail in the low-intensity range. Because confocal images suffer from background levels up to 30% maximum intensity, colocalization analysis, which is a typical segmentation process, is limited to high-intensity signal. In addition, noise-induced, false-positive events ("dust") may skew the results. Therefore, suppression of background is crucial for this type of image analysis. Analysis of synthetic and biological objects demonstrates that median filtering is able to eliminate noise-induced colocalization events successfully. Its disadvantages include the occasional generation of false-positive and false-negative results as well as the inherent impairment of resolution. In contrast, image restoration by deconvolution suppresses background to very low levels (