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ORCIDDaniel C. Castro
Daniel Coelho de Castro
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2020 – today
- 2025
[j2]Fernando Pérez-García, Harshita Sharma
, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Matthew P. Lungren, Maria Teodora Wetscherek, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, Ozan Oktay:
Exploring scalable medical image encoders beyond text supervision. Nat. Mac. Intell. 7(1): 119-130 (2025)- [c22]Ahmed Abdulaal, Chen Jin, Nina Montaña Brown, Aryo Pradipta Gema, Daniel C. Castro, Daniel C. Alexander, Philip Alexander Teare, Tom Diethe, Dino Oglic, Amrutha Saseendran:
Balancing Act: Diversity and Consistency in Large Language Model Ensembles. ICLR 2025 - [c21]Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz, Daniel C. Castro, Ben Glocker:
Rethinking Fair Representation Learning for Performance-Sensitive Tasks. ICLR 2025 - 2024
- [c20]Shaury Srivastav, Mercy Ranjit, Fernando Pérez-García, Kenza Bouzid, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Harshita Sharma, Maximilian Ilse, Valentina Salvatelli, Sam Bond-Taylor, Fabian Falck, Anja Thieme, Hannah Richardson, Matthew P. Lungren, Stephanie L. Hyland, Javier Alvarez-Valle:
MAIRA at RRG24: A specialised large multimodal model for radiology report generation. BioNLP@ACL 2024: 597-602 - [c19]Nur Yildirim, Hannah Richardson, Maria Teodora Wetscherek, Junaid Bajwa, Joseph Jacob, Mark Ames Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie L. Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme:
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. CHI 2024: 444:1-444:22 - [c18]Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel C. Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse:
RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing. ECCV (12) 2024: 358-376 - [c17]Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel C. Castro, Daniel C. Alexander:
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning. ICLR 2024 - [i31]Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Matthew P. Lungren, Maria Wetscherek, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, Ozan Oktay:
RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision. CoRR abs/2401.10815 (2024) - [i30]Nur Yildirim, Hannah Richardson, Maria T. A. Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A. Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie L. Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P. Lungren, Javier Alvarez-Valle, Aditya V. Nori, Anja Thieme:
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. CoRR abs/2402.14252 (2024) - [i29]Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson, Fernando Pérez-García, Stephanie L. Hyland, Shruthi Bannur, Daniel C. Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya V. Nori, Stephen Harris, Joseph Jacob:
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. CoRR abs/2405.05299 (2024) - [i28]Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P. Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie L. Hyland:
MAIRA-2: Grounded Radiology Report Generation. CoRR abs/2406.04449 (2024) - [i27]Ahmed Abdulaal, Hugo Fry, Nina Montaña Brown, Ayodeji Ijishakin, Jack Gao, Stephanie L. Hyland, Daniel C. Alexander, Daniel C. Castro:
An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation. CoRR abs/2410.03334 (2024) - [i26]Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz, Daniel C. Castro, Ben Glocker:
Rethinking Fair Representation Learning for Performance-Sensitive Tasks. CoRR abs/2410.04120 (2024) - [i25]Daniel C. Castro, Aurelia Bustos, Shruthi Bannur, Stephanie L. Hyland, Kenza Bouzid, Maria Teodora Wetscherek, M. Sánchez-Valverde, Lara Jaques-Pérez, Lourdes Pérez-Rodríguez, Kenji Takeda, José María Salinas, Javier Alvarez-Valle, Joaquin Galant, Antonio Pertusa:
PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation. CoRR abs/2411.05085 (2024) - [i24]Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel C. Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Prasanna Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson, Maria Teodora Wetscherek, Stephanie L. Hyland, Javier Alvarez-Valle:
MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models. CoRR abs/2411.11362 (2024) - 2023
- [c16]Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CVPR 2023: 15016-15027 - [c15]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. EMNLP 2023: 14414-14445 - [c14]Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker:
Measuring axiomatic soundness of counterfactual image models. ICLR 2023 - [i23]Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CoRR abs/2301.04558 (2023) - [i22]Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker:
Measuring axiomatic soundness of counterfactual image models. CoRR abs/2303.01274 (2023) - [i21]Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa D. McCradden, Ben Glocker:
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging. CoRR abs/2307.16526 (2023) - [i20]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. CoRR abs/2310.14573 (2023) - [i19]Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P. Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle:
MAIRA-1: A specialised large multimodal model for radiology report generation. CoRR abs/2311.13668 (2023) - [i18]Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel C. Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse:
RadEdit: stress-testing biomedical vision models via diffusion image editing. CoRR abs/2312.12865 (2023) - 2022
- [c13]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) 2022: 1-21 - [c12]Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker:
Deep Structural Causal Shape Models. ECCV Workshops (6) 2022: 400-432 - [c11]Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker:
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation. ML4H@NeurIPS 2022: 290-310 - [i17]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR abs/2204.09817 (2022) - [i16]Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker:
Deep Structural Causal Shape Models. CoRR abs/2208.10950 (2022) - [i15]Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker:
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation. CoRR abs/2211.01886 (2022) - 2021
- [i14]Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya V. Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel C. Castro:
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs. CoRR abs/2107.06618 (2021) - [i13]Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem Can Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya V. Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay:
Active label cleaning: Improving dataset quality under resource constraints. CoRR abs/2109.00574 (2021) - 2020
- [c10]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Ben Glocker:
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. MICCAI (7) 2020: 710-719 - [c9]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 - [c8]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. NeurIPS 2020 - [i12]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) - [i11]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. CoRR abs/2006.06485 (2020) - [i10]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
- [j1]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. J. Mach. Learn. Res. 20: 178:1-178:29 (2019) - [c7]Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker:
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. IPMI 2019: 221-234 - [c6]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. NeurIPS 2019: 6447-6458 - [i9]Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker:
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. CoRR abs/1903.02429 (2019) - [i8]Ben Glocker, Robert Robinson, Daniel Coelho de Castro, Qi Dou, Ender Konukoglu:
Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects. CoRR abs/1910.04597 (2019) - [i7]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. CoRR abs/1910.13580 (2019) - [i6]Daniel Coelho de Castro, Ian Walker, Ben Glocker:
Causality matters in medical imaging. CoRR abs/1912.08142 (2019) - 2018
- [c5]Daniel Coelho de Castro, Sebastian Nowozin:
From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data. ECCV (2) 2018: 764-780 - [c4]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 - [c3]Jo Schlemper, Daniel Coelho de Castro, Wenjia Bai, Chen Qin, Ozan Oktay, Jinming Duan, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Bayesian Deep Learning for Accelerated MR Image Reconstruction. MLMIR@MICCAI 2018: 64-71 - [c2]Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. MICCAI (1) 2018: 206-214 - [c1]Jo Schlemper, Ozan Oktay, Wenjia Bai, Daniel Coelho de Castro, Jinming Duan, Chen Qin, Joseph V. Hajnal, Daniel Rueckert:
Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning. MICCAI (1) 2018: 259-267 - [i5]Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. CoRR abs/1806.02613 (2018) - [i4]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) - [i3]Daniel Coelho de Castro, Sebastian Nowozin:
From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data. CoRR abs/1807.07872 (2018) - [i2]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. CoRR abs/1809.10780 (2018) - [i1]Daniel Coelho de Castro, Sebastian Nowozin:
Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model. CoRR abs/1811.07753 (2018)
Coauthor Index
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