31 citations · 64 across the 5 of their papers we have counts for
5 papers
Transformer-based normative modelling for anomaly detection of early schizophrenia
Pedro F Da Costa, Jessica Dafflon, Sergio Leonardo Mendes +5
Despite the impact of psychiatric disorders on clinical health, early-stage diagnosis remains a challenge. Machine learning studies have shown that classifiers tend to be overly na…
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…
Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling: A data-driven approach to Predict Brain Age from Cortical Anatomical Measures
Jessica Dafflon, Walter H. L Pinaya, Federico Turkheimer +7
The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to…