7 citations · 13 across the 3 of their papers we have counts for
3 papers
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images
Alessandro Fontanella, Grant Mair, Joanna Wardlaw +2
Segmentation masks of pathological areas are useful in many medical applications, such as brain tumour and stroke management. Moreover, healthy counterfactuals of diseased images c…
ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging
Alessandro Fontanella, Antreas Antoniou, Wenwen Li +4
In some medical imaging tasks and other settings where only small parts of the image are informative for the classification task, traditional CNNs can sometimes struggle to general…
Machine learning of neuroimaging to diagnose cognitive impairment and dementia: a systematic review and comparative analysis
Enrico Pellegrini, Lucia Ballerini, Maria del C. Valdes Hernandez +11
INTRODUCTION: Advanced machine learning methods might help to identify dementia risk from neuroimaging, but their accuracy to date is unclear. METHODS: We systematically reviewed t…