Konstantinos Kamnitsas
Associate Professor of Engineering Science
Develops deep neural networks for medical image analysis, with work on domain adaptation and reliability.
Konstantinos Kamnitsas's lab at Oxford works on medical imaging & healthcare AI. 24 papers since 2023, 6 at top venues, mostly TMI and BMVC. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 25%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 10 papers2025 · T1 4
- 7 papers2024 · T1 0
- 5 papers2023 · T1 2
T1 venuesOtherVenues: TMI, BMVC, CVPR, ICCV, Medical Image Analysis
Research focuspaper titles that use each topic's words
- Medical imaging & healthcare AI4 papers
- adaptation2 papers
- domain adaptation1 paper
- reliability1 paper
- deep neural0 papers
Paper list
From the lab homepage.
20262 papers
202510 papers
- NeurIPS (T1)DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging (opens in a new tab)
- —Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection (opens in a new tab)
- CVPR (T1)F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics (opens in a new tab)
- WACVFeasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities (opens in a new tab)
- —Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing (opens in a new tab)
- Medical Image Analysis (T1)IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI (opens in a new tab)
- —Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components (opens in a new tab)
- JAMA SurgeryRadiomics for Treatment Planning in Liver Cancers (opens in a new tab)
- ICCV (T1)SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation (opens in a new tab)
- ICCVWUnsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentation (opens in a new tab)
20247 papers
- —An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis (opens in a new tab)
- BMVCAs firm as their foundations: creating transferable adversarial examples across downstream tasks with CLIP
- International Conference on Medical Imaging with Deep LearningFeasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
- —IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI (opens in a new tab)
- International Workshop on Applications of Medical AIModality cycles with masked conditional diffusion for unsupervised anomaly segmentation in MRI (opens in a new tab)
- Lecture Notes in Computer SciencePreface DART 2023
- —Semi-Supervised Learning for Deep Causal Generative Models (opens in a new tab)
20235 papers
- Clinical OncologyA Review of the Metrics Used to Assess Auto-Contouring Systems in Radiotherapy (opens in a new tab)
- TMI (T1)Context Label Learning: Improving Background Class Representations in Semantic Segmentation. (opens in a new tab)
- TMI (T1)Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation. (opens in a new tab)
- 136-146On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging (opens in a new tab)
- Machine Learning in Medical Imaging International Workshop, MLMIPost-deployment adaptation with access to source data via federated learning and source-target remote gradient alignment (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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- The alumni list could not be found on the lab site.
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