Technical Program

September 22nd, 2022

SGT 11:50 Keynote Prof. Shanshan Wang

SGT 12:20 Oral Session 1 : Deep Learning for Magnetic Resonance Imaging

SGT 12:20 Rethinking the optimization process for self-supervised model-driven MRI reconstruction

SGT 12:29 NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data

SGT 12:38 Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations

SGT 12:47 High-Fidelity MRI Reconstruction with the Densely Connected Network Cascade and Feature Residual Data Consistency Priors

SGT 12:56 Metal artifact correction MRI using multi-contrast deep neural networks for diagnosis of degenerative spinal diseases

SGT 13:05 Segmentation-Aware MRI Reconstruction

SGT 13:14 MRI Reconstruction with Conditional Adversarial Transformers

SGT 13:23 Break

SGT 13:33 Keynote Prof. Jong Chul Ye

SGT 14:03 Oral Session 2 : Deep Learning for General Image Reconstruction

SGT 14:03 A Noise-level-aware Framework for PET Image Denoising

SGT 14:12 DuDoTrans: Dual-Domain Transformer for Sparse-View CT Reconstruction

SGT 14:21 Deep Denoising Network for X-Ray Fluoroscopic Image Sequences of Moving Objects

SGT 14:30 PP-MPI: A Deep Plug-and-Play Prior for Magnetic Particle Imaging Reconstruction

SGT 14:39 Learning while Acquisition: Towards Active Learning Framework for Beamforming in Ultrasound Imaging

SGT 14:48 DPDudoNet: Deep-Prior based Dual-domain Network for Low-dose Computed Tomography Reconstruction

SGT 14:57 MTD-GAN: Multi-Task Discriminator based Generative Adversarial Networks for Low-Dose CT Denoising

SGT 15:06 Uncertainty-Informed Bayesian PET Image Reconstruction using a Deep Image Prior

SGT 15:15 Closing Remarks