5 papers
Closed-loop coupling of personalised and foundation models for real-time treatment guidance with MRI
James Grover, Emily A. Hewson, Andrew Phair +5
Image-guided therapies, including radiotherapy, biopsy and deep brain stimulation, rely on real-time targeting of anatomical structures. However, in the presence of motion, imaging…
Enhancing Ultra-low-field MRI with Segmentation-guided Adversarial Learning
James Grover, Andrew Phair, Michael Ferraro +1
Ultra-low-field (ULF) MRI offers portable and low-cost imaging but suffers from poor image quality. To address this, we present our submission to the 2025 ULF Enhancement Challenge…
Two-stage Respiratory Motion-resolved Radial MR Image Reconstruction Using an Interpretable Deep Unrolled Network
Shanshan Shan, Hongli Chen, Yuhan Wei +12
Due to the prolonged MRI encoding process, respiratory motion can cause undesired artifacts and image blurring, degrading image quality and limiting clinical applications in abdomi…
Design and Construction of a Dedicated Radiolucent 8-element Flexible Radiofrequency (RF) Torso Coil for the 1.0T Australian MRI-Linac System
Mingyan Li, Ewald Weber, David E. J. Waddington +6
Magnetic resonance imaging-guided linear accelerators (MRI-Linacs) are an emerging treatment technology that enable online soft-tissue visualisation and adaptive radiotherapy. The…
Accelerating Low-field MRI: From Compressed Sensing to Deep Learning Reconstruction with CNNs and Transformers
Efrat Shimron, Shanshan Shan, James Grover +7
Portable, low-field Magnetic Resonance Imaging (MRI) scanners are increasingly being deployed in clinical settings. However, key barriers to their widespread use include low signal…