Publication: An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction
An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction
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Twyman, R., Arridge, S., Kereta, Z., Jin, B., Brusaferri, L., Ahn, S., Stearns, C. W., Hutton, B. F., Burger, I. A., Kotasidis, F., & Thielemans, K. (2022). An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. IEEE Transactions on Medical Imaging, 42(1), 29–41. https://doi.org/10.1109/TMI.2022.3203237
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Penalised PET image reconstruction algorithms are often accelerated during early iterations with the use of subsets. However, these methods may exhibit limit cycle behaviour at later iterations due to variations between subsets. Desirable converged images can be achieved for a subclass of these algorithms via the implementation of a relaxed step size sequence, but the heuristic selection of parameters will impact the quality of the image sequence and algorithm convergence rates. In this work, we demonstrate the adaption and applicatio
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- Twyman, Robert
- Arridge, Simon
- Kereta, Zeljko
- Jin, Bangti
- Brusaferri, Ludovica
- Ahn, Sangtae
- Stearns, Charles W
- Hutton, Brian F
- Burger, Irene A
- Kotasidis, Fotis
- Thielemans, Kris
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Twyman, R., Arridge, S., Kereta, Z., Jin, B., Brusaferri, L., Ahn, S., Stearns, C. W., Hutton, B. F., Burger, I. A., Kotasidis, F., & Thielemans, K. (2022). An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. IEEE Transactions on Medical Imaging, 42(1), 29–41. https://doi.org/10.1109/TMI.2022.3203237
