ArticleMedical image analysis2023
Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models.
Article in Medical image analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Morphometric Explanations for Deep Learning Based Neuroimaging Classifiers.Human brain mapping · 2026Article
- Integrating Anatomical Priors Into a Causal Diffusion Model.IEEE transactions on medical imaging · 2026Article
- Bone morphology as a significant risk factor for anterior cruciate ligament injury.NPJ digital medicine · 2026Article
- Bridging modalities with AI: a review of AI advances in multimodal biomedical imaging.Communications engineering · 2026Review
- Generating Novel Brain Morphology by Deforming Learned Templates.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- Neural Autoregressive Modeling of Brain Aging.Deep generative models : 5th MICCAI workshop, DGM4MICCAI 2025, held in conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings. DGM4MICCAI (Workshop) (5th : 2025 : Taejon-si, Korea) · 2026Article
- Cycle Diffusion Model for Counterfactual Image Generation.Predictive Intelligence in Medicine. PRIME (Workshop) · 2026Article
- Brain Latent Progression: Individual-based spatiotemporal disease progression on 3D Brain MRIs via latent diffusion.Medical image analysis · 2025Article
- Article
- Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis.Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2025Article
- Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings.NPJ digital medicine · 2025Article
- Pioneering new paths: the role of generative modelling in neurological disease research.Pflugers Archiv : European journal of physiology · 2025Review
- A technical assessment of latent diffusion for Alzheimer's Disease progression.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Unmasking the Clever Hans effect in AI models: shortcut learning, spurious correlations, and the path toward robust intelligence.Frontiers in artificial intelligence · 2025Review
- Deep generative classification of blood cell morphology.Nature machine intelligence · 2025Article
- Metadata-conditioned generative models to synthesize anatomically-plausible 3D brain MRIs.Medical image analysis · 2024Article
- Addressing fairness issues in deep learning-based medical image analysis: a systematic review.NPJ digital medicine · 2024Review
- Sex-Based Performance Disparities in Machine Learning Algorithms for Cardiac Disease Prediction: Exploratory Study.Journal of medical Internet research · 2024Article
- Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review.Journal of imaging · 2023Review
- Predicting mortality in acutely hospitalised older patients: the impact of model dimensionality.BMC medicine · 2023Article
Corrections and comments
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Authors and funding
7 authors.
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Abstract
We describe CounterSynth, a conditional generative model of diffeomorphic deformations that induce label-driven, biologically plausible changes in volumetric brain images. The model is intended to synthesise counterfactual training data augmentations for downstream discriminative modelling tasks where fidelity is limited by data imbalance, distributional instability, confounding, or underspecification, and exhibits inequitable performance across distinct subpopulations. Focusing on demographic attributes, we evaluate the quality of synthesised counterfactuals with voxel-based morphometry, classification and regression of the conditioning attributes, and the Fréchet inception distance. Examining downstream discriminative performance in the context of engineered demographic imbalance and confounding, we use UK Biobank and OASIS magnetic resonance imaging data to benchmark CounterSynth augmentation against current solutions to these problems. We achieve state-of-the-art improvements, both in overall fidelity and equity. The source code for CounterSynth is available at https://github.com/guilherme-pombo/CounterSynth.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.