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    • 3. 发明授权
    • Parameter-free denoising of complex MR images by iterative multi-wavelet thresholding
    • 通过迭代多小波阈值对复杂MR图像进行无参数去噪
    • US09569843B1
    • 2017-02-14
    • US14849391
    • 2015-09-09
    • Siemens Healthcare GmbH
    • Boris MailheMariappan S. NadarStephan Kannengiesser
    • G06K9/00G06T7/00G06T5/00G06T5/20G06T5/10G06T11/00
    • G06T5/10G01R33/5608G01R33/5611G06T5/002G06T5/20G06T2207/10088
    • A method for denoising Magnetic Resonance Imaging (MRI) data includes receiving a noisy image acquired using an MRI imaging device and determining a noise model comprising a non-diagonal covariance matrix based on the noisy image and calibration characteristics of the MRI imaging device. The noisy image is designated as the current best image. Then, an iterative denoising process is performed to remove noise from the noisy image. Each iteration of the iterative denoising process comprises (i) applying a bank of heterogeneous denoisers to the current best image to generate a plurality of filter outputs, (ii) creating an image matrix comprising the noisy image, the current best image, and the plurality of filter outputs, (iii) finding a linear combination of elements of the image matrix which minimizes a Stein Unbiased Risk Estimation (SURE) value for the linear combination and the noise model, (iv) designating the linear combination as the current best image, and (v) updating each respective denoiser in the bank of heterogeneous denoisers based on the SURE value. Following the iterative denoising process, the current best image is designated as a final denoised image.
    • 用于去噪磁共振成像(MRI)数据的方法包括接收使用MRI成像装置获取的噪声图像,并且基于噪声图像和MRI成像装置的校准特性来确定包括非对角协方差矩阵的噪声模型。 嘈杂的图像被指定为当前最佳图像。 然后,执行迭代去噪处理以从噪声图像中去除噪声。 迭代去噪过程的每次迭代包括(i)将一组异构去噪器应用于当前最佳图像以产生多个滤波器输​​出,(ii)创建包括噪声图像,当前最佳图像和多个滤波器输​​出的图像矩阵 的滤波器输出,(iii)找到使线性组合和噪声模型的斯坦因无偏差风险估计(SURE)值最小化的图像矩阵的元素的线性组合,(iv)将线性组合指定为当前最佳图像, 和(v)基于SURE值来更新异构去噪器组中的每个相应的去噪器。 在迭代去噪过程之后,将当前最佳图像指定为最终的去噪图像。