Bai ZiJian, Huang Jian
University College Cork, Room 1-57, First Floor, Western Gateway Building, Western Road, Cork, T12 XF62, Ireland.
J Struct Biol X. 2025 Feb 3;11:100121. doi: 10.1016/j.yjsbx.2025.100121. eCollection 2025 Jun.
In the single-particle Cryo-EM projection image classification, it is a common practice to apply the Fourier transform to the images and extract rotation-invariant features in the frequency domain. However, this process involves interpolation, which can reduce the accuracy of the results. In contrast, the non-uniform Fourier transform provides more direct and accurate computation of rotation-invariant features without the need for interpolation in the computation process. Leveraging the capabilities of the non-uniform discrete Fourier transform (NUDFT), we have developed an algorithm for the rotation-invariant classification. To highlight its potential and applicability in the field of single-particle Cryo-EM, we conducted a direct comparison with the traditional Fourier transform and other methods, demonstrating the superior performance of the NUDFT.
在单颗粒冷冻电镜投影图像分类中，对图像应用傅里叶变换并在频域中提取旋转不变特征是一种常见做法。然而，这个过程涉及插值，这会降低结果的准确性。相比之下，非均匀傅里叶变换在计算过程中无需插值就能更直接、准确地计算旋转不变特征。利用非均匀离散傅里叶变换（NUDFT）的能力，我们开发了一种用于旋转不变分类的算法。为了突出其在单颗粒冷冻电镜领域的潜力和适用性，我们与传统傅里叶变换及其他方法进行了直接比较，证明了NUDFT的卓越性能。
