6 papers
Biomechanics-informed Non-rigid Medical Image Registration and its Inverse Material Property Estimation with Linear and Nonlinear Elasticity
Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed +4
This paper investigates both biomechanical-constrained non-rigid medical image registrations and accurate identifications of material properties for soft tissues, using physics-inf…
Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images
Weixi Yi, Vasilis Stavrinides, Zachary M. C. Baum +5
We propose Boundary-RL, a novel weakly supervised segmentation method that utilises only patch-level labels for training. We envision the segmentation as a boundary detection probl…
Non-rigid Medical Image Registration using Physics-informed Neural Networks
Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed +4
Biomechanical modelling of soft tissue provides a non-data-driven method for constraining medical image registration, such that the estimated spatial transformation is considered b…
Rapid Lung Ultrasound COVID-19 Severity Scoring with Resource-Efficient Deep Feature Extraction
Pierre Raillard, Lorenzo Cristoni, Andrew Walden +6
Artificial intelligence-based analysis of lung ultrasound imaging has been demonstrated as an effective technique for rapid diagnostic decision support throughout the COVID-19 pand…
Meta-Registration: Learning Test-Time Optimization for Single-Pair Image Registration
Zachary MC Baum, Yipeng Hu, Dean C Barratt
Neural networks have been proposed for medical image registration by learning, with a substantial amount of training data, the optimal transformations between image pairs. These tr…
Learning Generalized Non-Rigid Multimodal Biomedical Image Registration from Generic Point Set Data
Zachary MC Baum, Tamas Ungi, Christopher Schlenger +2
Free Point Transformer (FPT) has been proposed as a data-driven, non-rigid point set registration approach using deep neural networks. As FPT does not assume constraints based on p…