44 citations · 181 across the 16 of their papers we have counts for
7 papers · 1 filter
A 3D generative model of pathological multi-modal MR images and segmentations
Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges +3
Generative modelling and synthetic data can be a surrogate for real medical imaging datasets, whose scarcity and difficulty to share can be a nuisance when delivering accurate deep…
InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model
Jueqi Wang, Jacob Levman, Walter Hugo Lopez Pinaya +3
High-resolution (HR) MRI scans obtained from research-grade medical centers provide precise information about imaged tissues. However, routine clinical MRI scans are typically in l…
Generative AI for Medical Imaging: extending the MONAI Framework
Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot +21
Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to he…
Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection
Ashay Patel, Petru-Danial Tudiosu, Walter H. L. Pinaya +4
Cancer is a highly heterogeneous condition that can occur almost anywhere in the human body. 18F-fluorodeoxyglucose is an imaging modality commonly used to detect cancer due to its…
Brain Imaging Generation with Latent Diffusion Models
Walter H. L. Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon +5
Deep neural networks have brought remarkable breakthroughs in medical image analysis. However, due to their data-hungry nature, the modest dataset sizes in medical imaging projects…
Morphology-preserving Autoregressive 3D Generative Modelling of the Brain
Petru-Daniel Tudosiu, Walter Hugo Lopez Pinaya, Mark S. Graham +10
Human anatomy, morphology, and associated diseases can be studied using medical imaging data. However, access to medical imaging data is restricted by governance and privacy concer…
Unsupervised Brain Anomaly Detection and Segmentation with Transformers
Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert Gray +4
Pathological brain appearances may be so heterogeneous as to be intelligible only as anomalies, defined by their deviation from normality rather than any specific pathological char…