Abstract:
A method for performing 2-dimensional discrete Fourier transform of a subject image data to be performed in one or more digital processors includes performing 1-dimensional fast Fourier transform on each row of the subject image data and 1-dimensional fast Fourier transform on each column of the subject image, and performing a simplified fast Fourier transform processing on the extracted boundary image without performing column-by-column 1-dimensional fast Fourier transform by: performing 1-dimensional fast Fourier transform only on a first column vector in the extracted boundary image data, using scaled column vectors to derive fast Fourier transform of remaining columns of the extracted boundary image data, and performing 1-dimensional fast Fourier transform on each row of the extracted boundary image data. Then, fast Fourier transform of a periodic component of the subject image data with edge-artifacts removed and fast Fourier transform of a smooth component of the subject image data are derived from results of steps (b) and (c).
Abstract:
Apparatus for improving a three-dimensional (3D) reconstruction of a sample is programmed to execute instructions including: removing uncorrelated noise in said 3D reconstruction with COMET or other regularization techniques; and removing correlated noise in said 3D reconstruction by applying an Extended Field Iterative Reconstruction Technique (EFIRT) procedure.
Abstract:
Computerized method and system for improving 3D reconstruction images involves applying the Extended Field Iterative Reconstruction Technique (EFIRT) to remove correlated noise, in addition to using COMET (constrained maximum relative entropy tomography) to eliminate uncorrelated noise, wherein the EFIRT is applied by performing a set of successive reconstructions on an extended field larger than a region of interest (ROI); and extracting and averaging the ROI from said set of successive reconstructions.