Search results (84)
« Back to PublicationsFedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
Journal article
Saha P. et al, (2026), Information Fusion, 130, 104080 - 104080
IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI.
Journal article
Liang Z. et al, (2026), Medical image analysis, 107
Specialised or Generic? Tokenization Choices for Radiology Language Models
Conference paper
Warr H. et al, (2026), Lecture Notes in Computer Science, 16146 LNCS, 62 - 70
FedPIA - Permuting and Integrating Adapters Leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning
Journal article
Saha P. et al, (2025), Proceedings of the AAAI Conference on Artificial Intelligence, 39, 20228 - 20236
Incongruent Multimodal Federated Learning for Medical Vision and Language-based Multi-label Disease Detection
Journal article
Saha P. et al, (2025), Proceedings of the AAAI Conference on Artificial Intelligence, 39, 28331 - 28339
Radiomics for Treatment Planning in Liver Cancers.
Journal article
Mian A. et al, (2025), JAMA surgery
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks
Conference paper
Hu A. et al, (2025)
Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing
Chapter
Kalabizadeh H. et al, (2025), 15266 LNCS, 155 - 165
Unsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentation
Conference paper
Kalabizadeh H. et al, (2025), Proceedings 2025 IEEE Cvf International Conference on Computer Vision Workshops Iccv W 2025, 1104 - 1114
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
Conference paper
Wagner F. et al, (2025), Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025, 357 - 367
F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
Conference paper
Saha P. et al, (2025), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 20006 - 20017
Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection
Chapter
Anthony H. and Kamnitsas K., (2025), 15167, 160 - 170
Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components
Chapter
Warr H. et al, (2025), 15167, 70 - 80
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?
Conference paper
Hu A. et al, (2024)
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?
Conference paper
Hu A. et al, (2024)
Is Your Style Transfer Doing Anything Useful? An Investigation Into Hippocampus Segmentation and the Role of Preprocessing
Preprint
Kalabizadeh H. et al, (2024)
Preface DART 2023
Journal article
Koch L. et al, (2024), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14293 LNCS, v - vi
IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI
Chapter
Liang Z. et al, (2024), 15008 LNCS, 339 - 348
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
Conference paper
Xu W. et al, (2024), Proceedings of Machine Learning Research, 250, 1771 - 1784
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment
Conference paper
Wagner F. et al, (2024), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14349 LNCS, 253 - 263