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Konstantinos Kamnitsas
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2020 – today
- 2024
- [c33]Hermione Warr, Yasin Ibrahim, Daniel R. McGowan, Konstantinos Kamnitsas:
Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components. UNSURE@MICCAI 2024: 70-80 - [c32]Harry Anthony, Konstantinos Kamnitsas
:
Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection. UNSURE@MICCAI 2024: 160-170 - [c31]Yasin Ibrahim, Hermione Warr, Konstantinos Kamnitsas:
Semi-Supervised Learning for Deep Causal Generative Models. MICCAI (12) 2024: 294-303 - [c30]Ziyun Liang, Xiaoqing Guo, J. Alison Noble, Konstantinos Kamnitsas:
$\mathrm {IterMask^2}$: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI. MICCAI (8) 2024: 339-348 - [c29]Marawan Elbatel, Konstantinos Kamnitsas, Xiaomeng Li:
An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis. MICCAI (1) 2024: 656-666 - [e5]Lisa M. Koch
Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. Lecture Notes in Computer Science 14293, Springer 2024, ISBN 978-3-031-45856-9 [contents] - [i43]Pramit Saha, Divyanshu Mishra, Felix Wagner
Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection. CoRR abs/2402.05294 (2024) - [i42]Anjun Hu, Jindong Gu, Francesco Pinto, Konstantinos Kamnitsas, Philip Torr:
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks? CoRR abs/2403.12693 (2024) - [i41]Yasin Ibrahim, Hermione Warr, Konstantinos Kamnitsas:
Semi-Supervised Learning for Deep Causal Generative Models. CoRR abs/2403.18717 (2024) - [i40]Wentian Xu, Matthew Moffat, Thalia Seale, Ziyun Liang, Felix Wagner
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation. CoRR abs/2405.18511 (2024) - [i39]Ziyun Liang, Xiaoqing Guo, J. Alison Noble, Konstantinos Kamnitsas:
IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI. CoRR abs/2406.02422 (2024) - [i38]Felix Wagner
Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities. CoRR abs/2406.11636 (2024) - [i37]Marawan Elbatel, Konstantinos Kamnitsas, Xiaomeng Li:
An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis. CoRR abs/2407.03018 (2024) - [i36]Hermione Warr, Yasin Ibrahim, Daniel R. McGowan, Konstantinos Kamnitsas:
Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components. CoRR abs/2407.21638 (2024) - [i35]Harry Anthony, Konstantinos Kamnitsas:
Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection. CoRR abs/2408.17337 (2024) - 2023
- [j10]Zeju Li
Context Label Learning: Improving Background Class Representations in Semantic Segmentation. IEEE Trans. Medical Imaging 42(6): 1885-1896 (2023) - [j9]Zeju Li
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation. IEEE Trans. Medical Imaging 42(11): 3323-3335 (2023) - [c28]Harry Anthony
On the Use of Mahalanobis Distance for Out-of-distribution Detection with Neural Networks for Medical Imaging. UNSURE@MICCAI 2023: 136-146 - [c27]Ziyun Liang, Harry Anthony
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI. MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI 2023: 168-181 - [c26]Felix Wagner
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment. MLMI@MICCAI (2) 2023: 253-263 - [i34]Zeju Li, Konstantinos Kamnitsas, Qi Dou, Chen Qin, Ben Glocker:
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation. CoRR abs/2305.19084 (2023) - [i33]Ziyun Liang, Harry Anthony, Felix Wagner, Konstantinos Kamnitsas
Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI. CoRR abs/2308.16150 (2023) - [i32]Felix Wagner, Zeju Li, Pramit Saha, Konstantinos Kamnitsas
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment. CoRR abs/2308.16735 (2023) - [i31]Harry Anthony, Konstantinos Kamnitsas
On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging. CoRR abs/2309.01488 (2023) - 2022
- [c25]Zeju Li, Konstantinos Kamnitsas
Estimating Model Performance Under Domain Shifts with Class-Specific Confidence Scores. MICCAI (8) 2022: 693-703 - [e4]Konstantinos Kamnitsas
Domain Adaptation and Representation Transfer - 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13542, Springer 2022, ISBN 978-3-031-16851-2 [contents] - [i30]Sebastian G. Popescu, David J. Sharp
Distributional Gaussian Processes Layers for Out-of-Distribution Detection. CoRR abs/2206.13346 (2022) - [i29]Zeju Li, Konstantinos Kamnitsas
Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores. CoRR abs/2207.09957 (2022) - [i28]Zeju Li, Konstantinos Kamnitsas
Context Label Learning: Improving Background Class Representations in Semantic Segmentation. CoRR abs/2212.08423 (2022) - 2021
- [j8]Zeju Li
Analyzing Overfitting Under Class Imbalance in Neural Networks for Image Segmentation. IEEE Trans. Medical Imaging 40(3): 1065-1077 (2021) - [c24]Sebastian G. Popescu, David J. Sharp
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation. IPMI 2021: 415-427 - [c23]Konstantinos Kamnitsas
Transductive Image Segmentation: Self-training and Effect of Uncertainty Estimation. DART/FAIR@MICCAI 2021: 79-89 - [c22]Christoph Berger, Magdalini Paschali, Ben Glocker, Konstantinos Kamnitsas
Confidence-Based Out-of-Distribution Detection: A Comparative Study and Analysis. UNSURE/PIPPI@MICCAI 2021: 122-132 - [c21]Gregory Filbrandt, Konstantinos Kamnitsas
Learning from Partially Overlapping Labels: Image Segmentation Under Annotation Shift. DART/FAIR@MICCAI 2021: 123-132 - [e3]Shadi Albarqouni
Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health - Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Lecture Notes in Computer Science 12968, Springer 2021, ISBN 978-3-030-87721-7 [contents] - [i27]Zeju Li, Konstantinos Kamnitsas, Ben Glocker:
Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation. CoRR abs/2102.10365 (2021) - [i26]Sebastian G. Popescu, David J. Sharp, James H. Cole, Konstantinos Kamnitsas, Ben Glocker:
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation. CoRR abs/2104.13756 (2021) - [i25]Christoph Berger, Magdalini Paschali, Ben Glocker, Konstantinos Kamnitsas:
Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis. CoRR abs/2107.02568 (2021) - [i24]Gregory Filbrandt, Konstantinos Kamnitsas, David Bernstein, Alexandra Taylor, Ben Glocker:
Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift. CoRR abs/2107.05938 (2021) - [i23]Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker:
Transductive image segmentation: Self-training and effect of uncertainty estimation. CoRR abs/2107.08964 (2021) - 2020
- [b1]Konstantinos Kamnitsas:
Advancing efficiency and robustness of neural networks for imaging. Imperial College London, UK, 2020 - [j7]Carlo Biffi
Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models. IEEE Trans. Medical Imaging 39(6): 2088-2099 (2020) - [c20]Robert Robinson, Qi Dou, Daniel Coelho de Castro
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. MICCAI (7) 2020: 710-719 - [c19]Ahmed E. Fetit, Amir Alansary, Lucilio Cordero-Grande, John Cupitt, Alice B. Davidson, A. David Edwards, Joseph V. Hajnal, Emer J. Hughes, Konstantinos Kamnitsas, Vanessa Kyriakopoulou, Antonios Makropoulos, Prachi A. Patkee, Anthony N. Price, Mary A. Rutherford, Daniel Rueckert:
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling. MIDL 2020: 241-261 - [c18]Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker:
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. NeurIPS 2020 - [e2]Shadi Albarqouni
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning - Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings. Lecture Notes in Computer Science 12444, Springer 2020, ISBN 978-3-030-60547-6 [contents] - [i22]Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker:
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. CoRR abs/2006.06015 (2020) - [i21]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Benjamin M. Glocker:
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks. CoRR abs/2006.16741 (2020)
2010 – 2019
- 2019
- [j6]Amir Alansary
Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Anal. 53: 156-164 (2019) - [c17]Miguel Monteiro, Konstantinos Kamnitsas
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation. BrainLes@MICCAI (1) 2019: 13-22 - [c16]Loïc Le Folgoc
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. IPMI 2019: 221-234 - [c15]Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas
Multiple Landmark Detection Using Multi-agent Reinforcement Learning. MICCAI (4) 2019: 262-270 - [c14]Zeju Li, Konstantinos Kamnitsas
Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation. MICCAI (3) 2019: 402-410 - [c13]Cheng Ouyang, Konstantinos Kamnitsas
Data Efficient Unsupervised Domain Adaptation For Cross-modality Image Segmentation. MICCAI (2) 2019: 669-677 - [c12]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. NeurIPS 2019: 6447-6458 - [e1]Qian Wang, Fausto Milletari, Hien Van Nguyen, Shadi Albarqouni
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data - First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings. Lecture Notes in Computer Science 11795, Springer 2019, ISBN 978-3-030-33390-4 [contents] - [i20]Loïc Le Folgoc
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. CoRR abs/1903.02429 (2019) - [i19]Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Ozan Oktay, Loïc Le Folgoc, Konstantinos Kamnitsas, Antonio de Marvao, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert:
Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling. CoRR abs/1907.00058 (2019) - [i18]Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz:
Multiple Landmark Detection using Multi-Agent Reinforcement Learning. CoRR abs/1907.00318 (2019) - [i17]Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert:
Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation. CoRR abs/1907.02766 (2019) - [i16]Zeju Li, Konstantinos Kamnitsas, Ben Glocker:
Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation. CoRR abs/1907.10982 (2019) - [i15]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. CoRR abs/1910.13580 (2019) - 2018
- [j5]Ozan Oktay
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation. IEEE Trans. Medical Imaging 37(2): 384-395 (2018) - [c11]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. ICML 2018: 2464-2473 - [c10]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. MICCAI (1) 2018: 277-285 - [c9]Yao Qin, Konstantinos Kamnitsas
Autofocus Layer for Semantic Segmentation. MICCAI (3) 2018: 603-611 - [i14]Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori:
Autofocus Layer for Semantic Segmentation. CoRR abs/1805.08403 (2018) - [i13]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy. CoRR abs/1806.00363 (2018) - [i12]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. CoRR abs/1806.02679 (2018) - [i11]Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. CoRR abs/1806.03228 (2018) - [i10]Jelmer M. Wolterink, Konstantinos Kamnitsas, Christian Ledig, Ivana Isgum:
Generative adversarial networks and adversarial methods in biomedical image analysis. CoRR abs/1810.10352 (2018) - [i9]Chaitanya Baweja, Ben Glocker, Konstantinos Kamnitsas:
Towards continual learning in medical imaging. CoRR abs/1811.02496 (2018) - 2017
- [j4]Konstantinos Kamnitsas
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Medical Image Anal. 36: 61-78 (2017) - [j3]Martin Rajchl
DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks. IEEE Trans. Medical Imaging 36(2): 674-683 (2017) - [j2]Vanya V. Valindria
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth. IEEE Trans. Medical Imaging 36(8): 1597-1606 (2017) - [j1]Christian F. Baumgartner
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound. IEEE Trans. Medical Imaging 36(11): 2204-2215 (2017) - [c8]Konstantinos Kamnitsas
Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks. IPMI 2017: 597-609 - [c7]Steven G. McDonagh
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging. CMMI/RAMBO/SWITCH@MICCAI 2017: 116-126 - [c6]Konstantinos Kamnitsas
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. BrainLes@MICCAI 2017: 450-462 - [i8]Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker:
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth. CoRR abs/1702.03407 (2017) - [i7]Steven G. McDonagh, Benjamin Hou, Konstantinos Kamnitsas, Ozan Oktay, Amir Alansary, Mary A. Rutherford, Joseph V. Hajnal, Bernhard Kainz:
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging. CoRR abs/1703.00035 (2017) - [i6]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Ricardo Guerrero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation. CoRR abs/1705.08302 (2017) - [i5]Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. CoRR abs/1711.01468 (2017) - 2016
- [c5]Konstantinos Kamnitsas
DeepMedic for Brain Tumor Segmentation. BrainLes@MICCAI 2016: 138-149 - [c4]Christian F. Baumgartner
Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks. MICCAI (2) 2016: 203-211 - [c3]Ozan Oktay, Wenjia Bai, Matthew C. H. Lee, Ricardo Guerrero, Konstantinos Kamnitsas
Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks. MICCAI (3) 2016: 246-254 - [c2]Amir Alansary, Konstantinos Kamnitsas
Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI. MICCAI (2) 2016: 589-597 - [c1]Archontis Giannakidis
Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images Using a Multi-Scale 3D Convolutional Neural Network. SITIS 2016: 42-46 - [i4]Konstantinos Kamnitsas, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, Ben Glocker:
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation. CoRR abs/1603.05959 (2016) - [i3]Martin Rajchl, Matthew C. H. Lee, Ozan Oktay, Konstantinos Kamnitsas, Jonathan Passerat-Palmbach, Wenjia Bai, Bernhard Kainz, Daniel Rueckert:
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks. CoRR abs/1605.07866 (2016) - [i2]Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Tara P. Fletcher, Sandra Smith, Lisa M. Koch, Bernhard Kainz, Daniel Rueckert:
Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound. CoRR abs/1612.05601 (2016) - [i1]Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks. CoRR abs/1612.08894 (2016)
Coauthor Index
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