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Flat-field correction technique for digital detectors

机译:数字探测器的平场校正技术

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Abstract: The effects of the stationary noise patterns and variable pixel responses that commonly occur with uniform exposure of digital detectors can be effectively reduced by simple 'flat- field' image processing methods. These methods are based upon a linear system response and the acquisition of an image (or images) acquired at a high exposure to create an inverse matrix of values that when applied to an uncorrected image, remove the effects of the stationary noise components. System performance is optimized when the correction image is totally free of statistical variations. However, the stationary noise patterns will not be effectively removed for flat-field images that are acquired at a relatively low exposure or for systems with non-linear response to incident exposure variations. A reduction in image quality occurs with the incomplete removal of the stationary noise patterns, resulting in a loss of detective quantum efficiency of the system. A more flexible approach to the global flat-field correction methodology is investigated using a pixel by pixel least squares fit to 'synthesize' a variable flat-field image based upon the pixel value (incident exposure) of the image to be corrected. All of the information is stored in two 'equivalent images' containing the slope and intercept parameters. The methodology provides an improvement in the detective quantum efficiency (DQE) due to the greater immunity of the stationary noise variation encoded in the slope/intercept parameters calculated on a pixel by pixel basis over a range of incident exposures. When the raw image contains a wide range of incident exposures (e.g., transmission through an object) the variable exposure flat-field correction methodology proposed here provides an improved match to the fixed-point noise superimposed in the uncorrected image, particularly for the higher spatial frequencies in the image as demonstrated by DQE(f) measurements. Successful application to clinical digital mammography biopsy images has been demonstrated, and benefit to other digital detectors appears likely. !8
机译:摘要:通过简单的“平场”图像处理方法,可以有效地减少固定噪声模式和可变像素响应(通常发生在数字检测器均匀曝光下)的影响。这些方法基于线性系统响应和在高曝光下获取的图像(或多个图像)的采集,以创建值的逆矩阵,当将其应用于未经校正的图像时,可以消除静态噪声分量的影响。当校正图像完全没有统计变化时,可以优化系统性能。但是,对于在相对较低的曝光下获取的平场图像或对入射曝光变化具有非线性响应的系统,将无法有效去除静态噪声模式。图像的质量下降会导致静态噪声图样无法完全消除,从而导致系统的检测量子效率下降。使用逐像素最小二乘拟合以基于要校正图像的像素值(入射曝光)“合成”可变平场图像,研究了一种更灵活的全局平场校正方法。所有信息都存储在两个包含斜率和截距参数的“等效图像”中。由于在入射曝光范围内,逐像素计算的斜率/截距参数中编码的平稳噪声变化具有更大的抗扰性,因此该方法提供了检测量子效率(DQE)的改进。当原始图像包含大范围的入射曝光(例如,通过物体的透射)时,此处提出的可变曝光平场校正方法可以更好地匹配未校正图像中叠加的定点噪声,特别是对于较高空间图像中的频率,如DQE(f)测量所示。已经证明了其在临床数字乳腺X线摄影活检图像中的成功应用,并且可能对其他数字检测器有利。 !8

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