Showing 50 publications by Konstantinos Kamnitsas
Specialised or Generic? Tokenization Choices for Radiology Language Models
Warr H, Xu W, Anthony H, Ibrahim Y, McGowan DR et al. (2026), Lecture Notes in Computer Science, 16146, 62-70
BibTeX
@inproceedings{specialisedorge-2026/,
title={Specialised or Generic? Tokenization Choices for Radiology Language Models},
author={Warr H, Xu W, Anthony H, Ibrahim Y, McGowan DR et al.},
pages={62-70},
year = "2026"
}
Unsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentation
Kalabizadeh H, Griffanti L, Yeung P-H, Namburete AIL, Dinsdale NK et al. (2025)
BibTeX
@misc{unsuperviseddom-2025/10,
title={Unsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentation},
author={Kalabizadeh H, Griffanti L, Yeung P-H, Namburete AIL, Dinsdale NK et al.},
year = "2025"
}
IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI
Liang Z, Guo X, Xu W, Ibrahim Y, Voets N et al. (2025), Medical Image Analysis, 103763-103763
BibTeX
@article{itermaskdunsupe-2025/8,
title={IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI},
author={Liang Z, Guo X, Xu W, Ibrahim Y, Voets N et al.},
journal={Medical Image Analysis},
number={103763},
pages={103763-103763},
publisher={Elsevier BV},
year = "2025"
}
Specialised or Generic? Tokenization Choices for Radiology Language Models
Warr H, Xu W, Anthony H, Ibrahim Y, McGowan D et al. (2025)
BibTeX
@misc{specialisedorge-2025/8,
title={Specialised or Generic? Tokenization Choices for Radiology Language Models},
author={Warr H, Xu W, Anthony H, Ibrahim Y, McGowan D et al.},
year = "2025"
}
DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging
Wagner F, Saha P, Anthony H, Noble JA & Kamnitsas K (2025)
BibTeX
@misc{disondecentrali-2025/6,
title={DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging},
author={Wagner F, Saha P, Anthony H, Noble JA & Kamnitsas K},
year = "2025"
}
F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
Saha P, Wagner F, Mishra D, Peng C, Thakur A et al. (2025), 00, 20006-20017
BibTeX
@inproceedings{focusfederatedf-2025/6,
title={F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics},
author={Saha P, Wagner F, Mishra D, Peng C, Thakur A et al.},
booktitle={2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
pages={20006-20017},
year = "2025"
}
IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR
Liang Z, Guo X, Xu W, Ibrahim Y, Voets N et al. (2025)
BibTeX
@misc{itermaskdunsupe-2025/4,
title={IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR},
author={Liang Z, Guo X, Xu W, Ibrahim Y, Voets N et al.},
year = "2025"
}
Continuous Online Adaptation Driven by User Interaction for Medical Image Segmentation
Xu W, Liang Z, Anthony H, Ibrahim Y, Cohen F et al. (2025)
BibTeX
@misc{continuousonlin-2025/3,
title={Continuous Online Adaptation Driven by User Interaction for Medical Image Segmentation},
author={Xu W, Liang Z, Anthony H, Ibrahim Y, Cohen F et al.},
year = "2025"
}
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Wagner F, Xu W, Saha P, Liang Z, Whitehouse D et al. (2025), 00, 357-367
BibTeX
@inproceedings{feasibilityoffe-2025/3,
title={Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities},
author={Wagner F, Xu W, Saha P, Liang Z, Whitehouse D et al.},
booktitle={2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
pages={357-367},
year = "2025"
}
Radiomics for Treatment Planning in Liver Cancers.
Mian A, Kamnitsas K & Gordon-Weeks A (2025), JAMA surgery
BibTeX
@article{radiomicsfortre-2025/2,
title={Radiomics for Treatment Planning in Liver Cancers.},
author={Mian A, Kamnitsas K & Gordon-Weeks A},
journal={JAMA surgery},
year = "2025"
}
Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection
Anthony H & Kamnitsas K (2025), 15167, 160-170
BibTeX
@misc{evaluatingrelia-2025/,
title={Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection},
author={Anthony H & Kamnitsas K},
year = "2025"
}
Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing
Kalabizadeh H, Griffanti L, Yeung P-H, Voets N, Gillis G et al. (2025), 15266, 155-165
BibTeX
@misc{isyourstyletran-2025/,
title={Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing},
author={Kalabizadeh H, Griffanti L, Yeung P-H, Voets N, Gillis G et al.},
year = "2025"
}
Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components
Warr H, Ibrahim Y, McGowan DR & Kamnitsas K (2025), 15167, 70-80
BibTeX
@misc{qualitycontrolf-2025/,
title={Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components},
author={Warr H, Ibrahim Y, McGowan DR & Kamnitsas K},
year = "2025"
}
As firm as their foundations: creating transferable adversarial examples across downstream tasks with CLIP
Hu A, Gu J, Pinto F, Kamnitsas K & Torr PHS (2024), Proceedings of the 35th British Machine Vision Conference (BMVC 2024)
BibTeX
@inproceedings{asfirmastheirfo-2024/12,
title={As firm as their foundations: creating transferable adversarial examples across downstream tasks with CLIP},
author={Hu A, Gu J, Pinto F, Kamnitsas K & Torr PHS},
booktitle={35th British Machine Vision Conference (BMVC 2024)},
year = "2024"
}
FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning
Saha P, Mishra D, Wagner F, Kamnitsas K & Noble JA (2024)
BibTeX
@misc{fedpiapermuting-2024/12,
title={FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning},
author={Saha P, Mishra D, Wagner F, Kamnitsas K & Noble JA},
year = "2024"
}
SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation
Zhu J, Wu J, Ouyang C, Kamnitsas K & Noble A (2024)
BibTeX
@misc{spaefficientuse-2024/11,
title={SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation},
author={Zhu J, Wu J, Ouyang C, Kamnitsas K & Noble A},
year = "2024"
}
F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
Saha P, Wagner F, Mishra D, Peng C, Thakur A et al. (2024)
BibTeX
@misc{focusfederatedf-2024/11,
title={F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics},
author={Saha P, Wagner F, Mishra D, Peng C, Thakur A et al.},
year = "2024"
}
Is your style transfer doing anything useful? an investigation into hippocampus segmentation and the role of preprocessing
Kalabizadeh H, Griffanti L, Yeung P-H, Voets N, Gillis G et al. (2024)
BibTeX
@misc{isyourstyletran-2024/8,
title={Is your style transfer doing anything useful? an investigation into hippocampus segmentation and the role of preprocessing},
author={Kalabizadeh H, Griffanti L, Yeung P-H, Voets N, Gillis G et al.},
year = "2024"
}
Evaluating reliability in medical DNNs: a critical analysis of feature and confidence-based OOD detection
Anthony H & Kamnitsas K (2024)
BibTeX
@misc{evaluatingrelia-2024/8,
title={Evaluating reliability in medical DNNs: a critical analysis of feature and confidence-based OOD detection},
author={Anthony H & Kamnitsas K},
year = "2024"
}
An organism starts with a single pix-cell: a neural cellular diffusion for high-resolution image synthesis
Elbatel M, Kamnitsas K & Li X (2024)
BibTeX
@misc{anorganismstart-2024/7,
title={An organism starts with a single pix-cell: a neural cellular diffusion for high-resolution image synthesis},
author={Elbatel M, Kamnitsas K & Li X},
year = "2024"
}
Quality control for radiology report generation models via auxiliary auditing components
Warr H, Ibrahim Y, McGowan DR & Kamnitsas K (2024)
BibTeX
@misc{qualitycontrolf-2024/7,
title={Quality control for radiology report generation models via auxiliary auditing components},
author={Warr H, Ibrahim Y, McGowan DR & Kamnitsas K},
year = "2024"
}
IterMask2: iterative unsupervised anomaly segmentation via spatial and frequency masking for brain lesions in MRI
Liang Z, Guo X, Noble JA & Kamnitsas K (2024)
BibTeX
@misc{itermaskiterati-2024/6,
title={IterMask2: iterative unsupervised anomaly segmentation via spatial and frequency masking for brain lesions in MRI},
author={Liang Z, Guo X, Noble JA & Kamnitsas K},
year = "2024"
}
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Wagner F, Xu W, Saha P, Liang Z, Whitehouse D et al. (2024)
BibTeX
@misc{feasibilityoffe-2024/6,
title={Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities},
author={Wagner F, Xu W, Saha P, Liang Z, Whitehouse D et al.},
year = "2024"
}
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
Xu W, Moffat M, Seale T, Liang Z, Wagner F et al. (2024)
BibTeX
@misc{feasibilityandb-2024/5,
title={Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation},
author={Xu W, Moffat M, Seale T, Liang Z, Wagner F et al.},
year = "2024"
}
Semi-supervised learning for deep causal generative models
Ibrahim Y, Warr H & Kamnitsas K (2024)
BibTeX
@misc{semisupervisedl-2024/3,
title={Semi-supervised learning for deep causal generative models},
author={Ibrahim Y, Warr H & Kamnitsas K},
year = "2024"
}
As firm as their foundations: can open-sourced foundation models be used to create adversarial examples for downstream tasks?
Hu A, Gu J, Pinto F, Kamnitsas K & Torr P (2024)
BibTeX
@misc{asfirmastheirfo-2024/3,
title={As firm as their foundations: can open-sourced foundation models be used to create adversarial examples for downstream tasks?},
author={Hu A, Gu J, Pinto F, Kamnitsas K & Torr P},
year = "2024"
}
Modality cycles with masked conditional diffusion for unsupervised anomaly segmentation in MRI
Liang Z, Anthony H, Wagner F & Kamnitsas K (2024), Proceedings of the 2nd International Workshop on Applications of Medical AI (MICCAI - AMAI 2023), 14394, 168-181
BibTeX
@inproceedings{modalitycyclesw-2024/2,
title={Modality cycles with masked conditional diffusion for unsupervised anomaly segmentation in MRI},
author={Liang Z, Anthony H, Wagner F & Kamnitsas K},
booktitle={2nd International Workshop on Applications of Medical AI (MICCAI - AMAI 2023)},
pages={168-181},
year = "2024"
}
Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection
Saha P, Mishra D, Wagner F, Kamnitsas K & Noble JA (2024)
BibTeX
@misc{examiningmodali-2024/2,
title={Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection},
author={Saha P, Mishra D, Wagner F, Kamnitsas K & Noble JA},
year = "2024"
}
Preface DART 2023
Koch L, Cardoso MJ, Ferrante E, Islam M, Jiang M et al. (2024), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14293 LNCS, v-vi
BibTeX
@article{prefacedart-2024/1,
title={Preface DART 2023},
author={Koch L, Cardoso MJ, Ferrante E, Islam M, Jiang M et al.},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume={14293 LNCS},
pages={v-vi},
year = "2024"
}
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
Xu W, Moffat M, Seale T, Liang Z, Wagner F et al. (2024), Proceedings of Machine Learning Research, 250, 1771-1784
BibTeX
@inproceedings{feasibilityandb-2024/1,
title={Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation},
author={Xu W, Moffat M, Seale T, Liang Z, Wagner F et al.},
pages={1771-1784},
year = "2024"
}
IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI
Liang Z, Guo X, Noble JA & Kamnitsas K (2024), 15008, 339-348
BibTeX
@misc{itermaskiterati-2024/,
title={IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI},
author={Liang Z, Guo X, Noble JA & Kamnitsas K},
year = "2024"
}
Semi-Supervised Learning for Deep Causal Generative Models
Ibrahim Y, Warr H & Kamnitsas K (2024), 15012, 294-303
BibTeX
@misc{semisupervisedl-2024/,
title={Semi-Supervised Learning for Deep Causal Generative Models},
author={Ibrahim Y, Warr H & Kamnitsas K},
year = "2024"
}
An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis
Elbatel M, Kamnitsas K & Li X (2024), 15001, 656-666
BibTeX
@misc{anorganismstart-2024/,
title={An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis},
author={Elbatel M, Kamnitsas K & Li X},
year = "2024"
}
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation.
Li Z, Kamnitsas K, Dou Q, Qin C & Glocker B (2023), IEEE transactions on medical imaging, 42(11), 3323-3335
BibTeX
@article{jointoptimizati-2023/11,
title={Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation.},
author={Li Z, Kamnitsas K, Dou Q, Qin C & Glocker B},
journal={IEEE transactions on medical imaging},
volume={42},
pages={3323-3335},
year = "2023"
}
Post-deployment adaptation with access to source data via federated learning and source-target remote gradient alignment
Wagner F, Li Z, Saha P & Kamnitsas K (2023), Machine Learning in Medical Imaging, 253-263
BibTeX
@inproceedings{postdeploymenta-2023/10,
title={Post-deployment adaptation with access to source data via federated learning and source-target remote gradient alignment},
author={Wagner F, Li Z, Saha P & Kamnitsas K},
booktitle={Machine Learning in Medical Imaging 14th International Workshop, MLMI 2023},
pages={253-263},
year = "2023"
}
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging
Anthony H & Kamnitsas K (2023), 136-146
BibTeX
@misc{ontheuseofmahal-2023/10,
title={On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging},
author={Anthony H & Kamnitsas K},
year = "2023"
}
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging
Anthony H & Kamnitsas K (2023)
BibTeX
@misc{ontheuseofmahal-2023/9,
title={On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging},
author={Anthony H & Kamnitsas K},
year = "2023"
}
Post-deployment adaptation with access to source data via federated learning and source-target remote gradient alignment
Wagner F, Li Z, Saha P & Kamnitsas K (2023)
BibTeX
@misc{postdeploymenta-2023/8,
title={Post-deployment adaptation with access to source data via federated learning and source-target remote gradient alignment},
author={Wagner F, Li Z, Saha P & Kamnitsas K},
year = "2023"
}
Modality cycles with masked conditional diffusion for unsupervised anomaly segmentation in MRI
Liang Z, Anthony H, Wagner F & Kamnitsas K (2023)
BibTeX
@misc{modalitycyclesw-2023/8,
title={Modality cycles with masked conditional diffusion for unsupervised anomaly segmentation in MRI},
author={Liang Z, Anthony H, Wagner F & Kamnitsas K},
year = "2023"
}
A Review of the Metrics Used to Assess Auto-Contouring Systems in Radiotherapy.
Mackay K, Bernstein D, Glocker B, Kamnitsas K & Taylor A (2023), Clinical oncology (Royal College of Radiologists (Great Britain)), 35(6), 354-369
BibTeX
@article{areviewofthemet-2023/6,
title={A Review of the Metrics Used to Assess Auto-Contouring Systems in Radiotherapy.},
author={Mackay K, Bernstein D, Glocker B, Kamnitsas K & Taylor A},
journal={Clinical oncology (Royal College of Radiologists (Great Britain))},
volume={35},
pages={354-369},
year = "2023"
}
Context Label Learning: Improving Background Class Representations in Semantic Segmentation.
Li Z, Kamnitsas K, Ouyang C, Chen C & Glocker B (2023), IEEE transactions on medical imaging, 42(6), 1885-1896
BibTeX
@article{contextlabellea-2023/6,
title={Context Label Learning: Improving Background Class Representations in Semantic Segmentation.},
author={Li Z, Kamnitsas K, Ouyang C, Chen C & Glocker B},
journal={IEEE transactions on medical imaging},
volume={42},
pages={1885-1896},
year = "2023"
}
Joint optimization of class-specific training- and test-time data augmentation in segmentation
Li Z, Kamnitsas K, Dou Q, Qin C & Glocker B (2023)
BibTeX
@misc{jointoptimizati-2023/5,
title={Joint optimization of class-specific training- and test-time data augmentation in segmentation},
author={Li Z, Kamnitsas K, Dou Q, Qin C & Glocker B},
year = "2023"
}
Context label learning: improving background class representations in semantic segmentation
Li Z, Kamnitsas K, Ouyang C, Chen C & Glocker B (2022)
BibTeX
@misc{contextlabellea-2022/12,
title={Context label learning: improving background class representations in semantic segmentation},
author={Li Z, Kamnitsas K, Ouyang C, Chen C & Glocker B},
year = "2022"
}
Federated learning enables big data for rare cancer boundary detection.
Pati S, Baid U, Edwards B, Sheller M, Wang S-H et al. (2022), Nature communications, 13(1), 7346-7346
BibTeX
@article{federatedlearni-2022/12,
title={Federated learning enables big data for rare cancer boundary detection.},
author={Pati S, Baid U, Edwards B, Sheller M, Wang S-H et al.},
journal={Nature communications},
volume={13},
pages={7346-7346},
year = "2022"
}
Estimating model performance under domain shifts with class-specific confidence scores
Li Z, Kamnitsas K, Islam M, Chen C & Glocker B (2022), Proceedings of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022), 693-703
BibTeX
@inproceedings{estimatingmodel-2022/9,
title={Estimating model performance under domain shifts with class-specific confidence scores},
author={Li Z, Kamnitsas K, Islam M, Chen C & Glocker B},
booktitle={25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022)},
pages={693-703},
year = "2022"
}
Estimating model performance under domain shifts with class-specific confidence scores
Li Z, Kamnitsas K, Islam M, Chen C & Glocker B (2022)
BibTeX
@misc{estimatingmodel-2022/7,
title={Estimating model performance under domain shifts with class-specific confidence scores},
author={Li Z, Kamnitsas K, Islam M, Chen C & Glocker B},
year = "2022"
}
Distributional Gaussian Processes layers for out-of-distribution detection
Popescu SG, Sharp DJ, Cole JH, Kamnitsas K & Glocker B (2022), MELBA Journal, 1(IPMI 2021), 1-64
BibTeX
@article{distributionalg-2022/6,
title={Distributional Gaussian Processes layers for out-of-distribution detection},
author={Popescu SG, Sharp DJ, Cole JH, Kamnitsas K & Glocker B},
journal={MELBA Journal},
volume={1},
pages={1-64},
publisher={Machine Learning for Biomedical Imaging},
year = "2022"
}
Distributional Gaussian Processes layers for out-of-distribution detection
Popescu SG, Sharp DJ, Cole JH, Kamnitsas K & Glocker B (2022)
BibTeX
@misc{distributionalg-2022/6,
title={Distributional Gaussian Processes layers for out-of-distribution detection},
author={Popescu SG, Sharp DJ, Cole JH, Kamnitsas K & Glocker B},
year = "2022"
}
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS et al. (2022), BMJ, 377
BibTeX
@article{reportingguidel-2022/5,
title={Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI},
author={Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS et al.},
journal={BMJ},
volume={377},
number={e070904},
publisher={BMJ Publishing Group},
year = "2022"
}
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.
Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS et al. (2022), Nature medicine, 28(5), 924-933
BibTeX
@article{reportingguidel-2022/5,
title={Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.},
author={Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS et al.},
journal={Nature medicine},
volume={28},
pages={924-933},
year = "2022"
}