Bernhard Kainz
Professor in Medical Image Computing
Heads the human-in-the-loop computing group and co-leads BioMedIA, developing machine learning for diagnostic decision-making and real-time fetal ultrasound analysis.
Bernhard Kainz's lab at Imperial works on medical imaging & healthcare AI, reinforcement learning and rendering & appearance. 104 papers since 2023. 22 PhD students and 4 master's students. 34 alumni. Applications close .
At a glance
- papers, 2023–2026
- 27/ year
- at T1 venues
- 0%
- PhD students
- 22
- MS students
- 4
- alumni listed
- 34
Papers by yearfrom the lab homepage, 2023–2026
- 17 papers2026 · T1 0 · collecting
- 30 papers2025 · T1 0
- 30 papers2024 · T1 0
- 27 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- Medical imaging & healthcare AI29 papers
- Reinforcement learning10 papers
- fetal8 papers
- Rendering & appearance0 papers
- human-in-the-loop0 papers
Paper list
From the lab homepage.
202617 papers
- Top JournalAbdominal simultaneous 3D water T1 and T2 mapping using a free-breathing Cartesian acquisition with spiral profile ordering (opens in a new tab)
- Top ConferenceCPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association
- Top ConferenceCRAgents for Disease Modelling via Multi-Agent Critique and Refinement
- Top ConferenceCTTok: Voxel-abulary for Autoregressive 3D CT Volume Generation with Large Language Models
- Bildverarbeitung für die Medizin : Proceedings, German Conference on Medical Image Computing, Luebeck March 15-17Distil or Cluster?
- BVM WorkshopDistil or Cluster? Data-efficient Learning for Ultrasound in Practice
- Top ConferenceFibers of Asymmetric Similarity: A Framework for Clinical and Imaging Data
- Top JournalGeneralist foundation models from a multimodal dataset for 3D computed tomography
- Top JournalHAMAgent: human assisted multiagent system for emotion recognition and digital health---a survey and preliminary study
- Top JournalImage-conditioned latent rectified flow models for 3D medical anomaly localisation
- Top ConferenceLearning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM
- Top ConferenceMulti-Camera AR Guidance System for Surgical Instrument Handling and Assembly: Investigating Workload and Efficiency
202530 papers
- Top JournalAI to Assist in the Fetal Anomaly Ultrasound Scan: A Randomized Controlled Trial (opens in a new tab)
- Top JournalArtificial Intelligence--Assisted Image Extraction in Neonatal Echocardiography for Congenital Heart Disease Diagnosis in Sub-Saharan Africa: Protocol for Model Development (opens in a new tab)
- Top JournalAutomatic Segmentation of Lymphatic Perfusion Pattern in Fontan Patients (opens in a new tab)
- Top ConferenceCan Diffusion Models Generalize? Privacy and Fairness Trade-offs for Medical Data Sharing
- —Causal reasoning in medical imaging (opens in a new tab)
- Top ConferenceCTFlow: Video-Inspired Latent Flow Matching for 3D CT Synthesis (opens in a new tab)
- Top JournalDiff-def: Diffusion-generated deformation fields for conditional atlases (opens in a new tab)
- MICCAI WorkshopDiffusing the Blind Spot: Uterine MRI Synthesis with Diffusion Models (opens in a new tab)
- Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning: First International Workshop, BRIDGE , and International Workshop, DeCaF , Held in Conjunction with MICCAI , Daejeon, South Korea, September 23 and September 27, , ProceedingsEnabling PSO-Secure Synthetic Data Sharing Using Diversity-Aware Diffusion
- Top ConferenceEnabling PSO-secure synthetic data sharing using diversity-aware diffusion models (opens in a new tab)
- Top ConferenceGenerate to Ground: Multimodal Text Conditioning Boosts Phrase Grounding in Medical Vision-Language Models (opens in a new tab)
- International Workshop on Reconstruction and Imaging Motion EstimationGraph Conditioned Diffusion for Controllable Histopathology Image Generation (opens in a new tab)
202430 papers
- BVM WorkshopAutomatic Segmentation of Lymphatic Perfusion in Patients with Congenital Single Ventricle Defects (opens in a new tab)
- —Biomedical Image Registration: 11th International Workshop, WBIR 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings
- Top ConferenceData-Efficient Generation for Dataset Distillation (opens in a new tab)
- Top ConferenceDisyre: Diffusion-inspired synthetic restoration for unsupervised anomaly detection (opens in a new tab)
- Top ConferenceEchonet-synthetic: Privacy-preserving video generation for safe medical data sharing (opens in a new tab)
- Top JournalEP01. 08: Artificial intelligence to assist in the screening fetal anomaly ultrasound scan (PROMETHEUS): a randomised controlled trial
- Top JournalExploring the role of different cell types on cortical folding in the developing human brain through computational modeling (opens in a new tab)
- Top ConferenceFAPI-PET/CT as a Predictor of Accelerated Lung Function Deterioration in Systemic Sclerosis Related Interstitial Lung Disease (ILD): Preliminaryinterim Analysis from a Confirmatory Risk Factor Study
- Top ConferenceImage distillation for safe data sharing in histopathology (opens in a new tab)
- International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical ImagingImage-conditioned diffusion models for medical anomaly detection (opens in a new tab)
- Top JournalInteraction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance? (opens in a new tab)
- Top JournalMetrics reloaded: recommendations for image analysis validation
202327 papers
- Top JournalAutomated ultrasound feature extraction in adnexal masses
- Top ConferenceBORS/BJR TRAVELLING FELLOWSHIP ABSTRACT: MOTION CAPTURE OF NEONATAL INFANT KICKING MOVEMENTS CAN PROVIDE AN EARLY PREDICTION OF CEREBRAL PALSY (opens in a new tab)
- Top ConferenceConditional temporal attention networks for neonatal cortical surface reconstruction (opens in a new tab)
- International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical ImagingConfidence-aware and self-supervised image anomaly localisation (opens in a new tab)
- —Counterfactual Data Augmentation for Deep Learning Predictive Models
- Top JournalEstimating categorical counterfactuals via deep twin networks (opens in a new tab)
- Top JournalFast fetal head compounding from multi-view 3D ultrasound (opens in a new tab)
- Top ConferenceFeature-conditioned cascaded video diffusion models for precise echocardiogram synthesis (opens in a new tab)
- Top ConferenceForeground-background separation through concept distillation from generative image foundation models (opens in a new tab)
- —HPI Future SOC Lab--Proceedings 2018
- Top JournalImproving image labelling quality (opens in a new tab)
- BVM WorkshopKeynote: Beyond Supervised Learning: Exploring Novel Machine Learning Approaches for Robust Medical Image Analysis (opens in a new tab)
Where alumni went34 listed
Apply to Imperial2027 (Apr/Oct)
Computing PhD
- Round
- Round 2 (1 Dec 2026)
- Opens
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- GRE
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- English
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- Fee
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