20 citations · 25 across the 4 of their papers we have counts for
4 papers
Penalized PET/CT Reconstruction Algorithms with Automatic Realignment for Anatomical Priors
Yu-Jung Tsai, Alexandre Bousse, Simon Arridge +3
Two algorithms for solving misalignment issues in penalized PET/CT reconstruction using anatomical priors are proposed. Both approaches are based on a recently published joint moti…
Improved MR to CT synthesis for PET/MR attenuation correction using Imitation Learning
Kerstin Kläser, Thomas Varsavsky, Pawel Markiewicz +6
The ability to synthesise Computed Tomography images - commonly known as pseudo CT, or pCT - from MRI input data is commonly assessed using an intensity-wise similarity, such as an…
Deep Boosted Regression for MR to CT Synthesis
Kerstin Kläser, Pawel Markiewicz, Marta Ranzini +7
Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification. However, attenuation correction…
What is the distribution of the number of unique original items in a bootstrap sample?
Alex F. Mendelson, Maria A. Zuluaga, Brian F. Hutton +1
Sampling with replacement occurs in many settings in machine learning, notably in the bagging ensemble technique and the .632+ validation scheme. The number of unique original item…