1 code implementation • 27 Aug 2023 • Imraj RD Singh, Alexander Denker, Riccardo Barbano, Željko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon Arridge
Score-based generative models have demonstrated highly promising results for medical image reconstruction tasks in magnetic resonance imaging or computed tomography.
no code implementations • 14 Jul 2021 • Arkadiusz Sitek, Sangtae Ahn, Evren Asma, Adam Chandler, Alvin Ihsani, Sven Prevrhal, Arman Rahmim, Babak Saboury, Kris Thielemans
Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications.
no code implementations • 21 Aug 2019 • Kerstin Kläser, Thomas Varsavsky, Pawel Markiewicz, Tom Vercauteren, David Atkinson, Kris Thielemans, Brian Hutton, M. Jorge Cardoso, Sebastien Ourselin
Quantitative results show that the network generates pCTs that seem less accurate when evaluating the Mean Absolute Error on the pCT (69. 68HU) compared to a baseline CNN (66. 25HU), but lead to significant improvement in the PET reconstruction - 115a. u.
no code implementations • 22 Aug 2018 • Kerstin Kläser, Pawel Markiewicz, Marta Ranzini, Wenqi Li, Marc Modat, Brian F. Hutton, David Atkinson, Kris Thielemans, M. Jorge Cardoso, Sebastien Ourselin
Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification.