Konstantinos Kamnitsas
Orcid: 0000-0003-3281-6509
According to our database1,
Konstantinos Kamnitsas
authored at least 55 papers
between 2016 and 2024.
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Bibliography
2024
Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components.
CoRR, 2024
An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis.
CoRR, 2024
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities.
CoRR, 2024
IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI.
CoRR, 2024
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation.
CoRR, 2024
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?
CoRR, 2024
Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection.
CoRR, 2024
2023
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation.
IEEE Trans. Medical Imaging, November, 2023
Context Label Learning: Improving Background Class Representations in Semantic Segmentation.
IEEE Trans. Medical Imaging, June, 2023
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
On the Use of Mahalanobis Distance for Out-of-distribution Detection with Neural Networks for Medical Imaging.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023
2022
CoRR, 2022
Estimating Model Performance Under Domain Shifts with Class-Specific Confidence Scores.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
Analyzing Overfitting Under Class Imbalance in Neural Networks for Image Segmentation.
IEEE Trans. Medical Imaging, 2021
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021
Learning from Partially Overlapping Labels: Image Segmentation Under Annotation Shift.
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis, 2021
Proceedings of the Information Processing in Medical Imaging, 2021
2020
IEEE Trans. Medical Imaging, 2020
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Medical Image Anal., 2019
Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing.
Proceedings of the Information Processing in Medical Imaging, 2019
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
2018
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation.
IEEE Trans. Medical Imaging, 2018
Generative adversarial networks and adversarial methods in biomedical image analysis.
CoRR, 2018
CoRR, 2018
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth.
IEEE Trans. Medical Imaging, 2017
DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks.
IEEE Trans. Medical Imaging, 2017
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound.
IEEE Trans. Medical Imaging, 2017
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation.
Medical Image Anal., 2017
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation.
CoRR, 2017
Proceedings of the Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment, 2017
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks.
Proceedings of the Information Processing in Medical Imaging, 2017
2016
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks.
CoRR, 2016
Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound.
CoRR, 2016
Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network.
Proceedings of the 12th International Conference on Signal-Image Technology & Internet-Based Systems, 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016
Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016