PSMR2024 10th Conference on PET, SPECT, and MR Multimodal Technologies, Total Body and Fast Timing in Medical Imaging

Session

Special Track on Image reconstruction

22 May 2024, 17:40

La Biodola, Isola d'Elba

Conveners

Special Track on Image reconstruction

• Johan Nuyts (KU Leuven, Belgium)
• Kris Thielemans (University College London)

11. Fast and memory-efficient reconstruction of sparse Poisson data in listmode with non-smooth priors with application to time-of-flight PET

Georg Schramm (KU Leuven)

22/05/2024, 17:40

[Special track] Advanced reconstruction algorithms

Oral

TOF sinograms of TOF PET scanners have a large memory footprint. Currently, they contain ~4e9 data bins which amount to ~17GB in single precision. Using iterative algorithms to reconstruct such enormous TOF sinograms becomes challenging due to the memory requirements and the time needed to evaluate the forward model. This is especially true for more advanced optimization algorithms such as the...

84. Stochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction

Evangelos Papoutsellis (Science and Technology Facilities Council), Margaret Duff (Science and Technology Facilities Council – Rutherford Appleton Laboratories)

22/05/2024, 17:55

[Special track] Advanced reconstruction algorithms

Oral

This study introduces a flexible, plug-and-play style stochastic optimization framework into the Core Imaging Library (CIL), facilitating the development and evaluation of diverse stochastic algorithms for image reconstruction tasks.

By plugging stochastic gradient estimators into base algorithms (including gradient descent and ISTA), we can produce a range of stochastic algorithms,...

90. Comparison of Synergistic and Single Modality Anatomically-Informed Structural Priors for Yttrium-90 PET and SPECT Reconstruction

Sam Porter (National Physical Laboratory & Institute of Nuclear Medicince, UCL)

22/05/2024, 18:10

[Special track] Advanced reconstruction algorithms

Oral

This research presents a synergistic method for the combined reconstruction of PET/CT and SPECT/CT data, aimed at improving image quality for Selective Internal Radiotherapy (SIRT) in treating unresectable liver tumours using Yttrium-90 ($^{90}Y$) microspheres. Given the challenges posed by sparse positron emissions in PET and the wide energy spectrum and electron range of bremsstrahlung...

69. Primal-Dual Hybrid Gradient Algorithm for emission tomography: A Comparative Study of Convergence under Poisson Likelihood with ML-EM

Luca Presotto (University of Milano Bicocca)

22/05/2024, 18:25

[Special track] Advanced reconstruction algorithms

Oral

The Primal-Dual Hybrid Gradient Algorithm (PDHG) holds relevance in image reconstruction due to its ability to implement non-smooth penalties. This algorithm also serves as the base for the “learned primal dual” method, which enables an AI-based, physics-inspired reconstruction. A unique challenge in emission tomography is that the optimization metric is the Poisson-likelihood, which often...

116. Announcement of the forthcoming SyneRBI PET Rapid Image Reconstruction Challenge

Kris Thielemans (University College London)

22/05/2024, 18:40

Oral

The Collaborative Computational Platform for Synergistic Reconstruction for Biomedical Imaging (https://www.ccpsynerbi.ac.uk/) is organising an open challenge for fast reconstruction of PET data with a given MAP objective function. Its primary aim is to stimulate research for the development of fast PET image reconstruction algorithms applicable to real world data. Motivated by the success of...