The Fourier reconstruction of a head section

By L. Shepp, B. Logan. 1974

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In Medical Imaging

Citations in the corpus

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains (2020, methodology): “We use two datasets for our 2D CT task: randomized Shepp-Logan phantoms [36], and the ATLAS brain dataset [21].”
Nonuniform fast Fourier transforms using min-max interpolation (2003, methodology): “To illustrate the accuracy of the NUFFT method in a practical context, we considered the classical 128 128 Shepp–Logan image [62], [63].”
Learned Initializations for Optimizing Coordinate-Based Neural Representations (2020, methodology): “T is a dataset of 2048 randomly generated 256× 256 pixel Shepp-Logan phantoms [31], where we provide 2D integral projections of a bundle of 256 parallel rays from a random angle as the measurement for each sampled signal T during meta-learning.”
Slice-to-volume medical image registration: a survey (2017, methodology): “(2010) or the well-known analytical Shepp-Logan phantom (Shepp and Logan, 1974) adopted by Kim et al.”
Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction (2013, background): “D Shepp-Logan phantom of size 128 × 128 × 128 voxels.”
Measuring techniques in gas–liquid and gas–liquid–solid reactors (2002, background): “Shepp and Logan (1974) proposed the following lter function g(S):”
Roxels: responsibility weighted 3D volume reconstruction (1999, methodology): “The simplification allows reconstruction to be performed with efficient linear methods [7, 4, 9].”
Multiscale X-ray tomography of cementitious materials: A review (2020, methodology): “convolve each projection with a discrete filter that approximates the ramp filter in Fourier space [48],”
Fast Alternating Direction Optimization Methods (2014, background): “The first problem is to reconstruct a synthetic image, the digital Shepp–Logan phantom [46], from undersampled data.”
Neural Network with Unbounded Activation Functions is Universal Approximator (2015, methodology): “We next studied a gray-scale image Shepp-Logan phantom [42].”
Density measurements using the Background Oriented Schlieren technique (2004, methodology): “…a sinc function (which is the continuous inverse Fourier transform of a rectangular pulse of width 2p and height unity) with the ramp filter (Shepp and Logan 1974): H xð Þ ¼ p xj j sin c x=xmaxð Þ xj j6xmax 0 xj j6xmax ð5Þ This filter results in a small amount of blurring, but is much less…”