I am Professor in Machine Learning for Imaging co-leading the Biomedical Image Analysis Group. I lead the HeartFlow-Imperial Research Team and I am also Head of ML Research at Kheiron Medical Technologies.
My research is at the intersection of medical imaging and artificial intelligence aiming to build safe and ethical computational tools for improving image-based detection and diagnosis of disease.
et al., 2023, Algorithmic encoding of protected characteristics in chest X-ray disease detection models, Ebiomedicine, ISSN:2352-3964
et al., 2022, UK National Screening Committee's approach to reviewing evidence on artificial intelligence in breast cancer screening, The Lancet Digital Health, Vol:4, ISSN:2589-7500, Pages:e558-e565
Bernhardt M, Jones C, Glocker B, 2022, Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms, Nature Medicine, Vol:28, ISSN:1078-8956, Pages:1157-+
et al., 2022, The medical algorithmic audit., The Lancet Digital Health, Vol:4, ISSN:2589-7500, Pages:e384-e397
et al., 2022, Active label cleaning for improved dataset quality under resource constraints, Nature Communications, Vol:13
et al., 2020, Atlas-ISTN: joint segmentation, registration and Atlas construction with image-and-spatial transformer networks
Coelho De Castro D, Walker I, Glocker B, 2020, Causality matters in medical imaging, Nature Communications, Vol:11, ISSN:2041-1723, Pages:1-10
et al., 2020, Multi-class semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning – an algorithm development and multi-centre validation study, The Lancet. Digital Health, Vol:2, ISSN:2589-7500, Pages:e314-e322
et al., 2019, Attention gated networks: Learning to leverage salient regions in medical images., Med Image Anal, Vol:53, Pages:197-207
Pawlowski N, Castro DC, Glocker B, Deep structural causal models for tractable counterfactual inference, Neural Information Processing Systems (NeurIPS), arXiv
et al., 2020, Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty, Curran Associates, Inc., Pages:12756-12767