Daniel C. Castro

According to our database, Daniel C. Castro authored at least 27 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology.

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

CoRR, 2024

RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision.

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

CoRR, 2024

2023

RadEdit: stress-testing biomedical vision models via diffusion image editing.

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

CoRR, 2023

MAIRA-1: A specialised large multimodal model for radiology report generation.

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

CoRR, 2023

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging.

Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa D. McCradden, Ben Glocker

CoRR, 2023

Measuring axiomatic soundness of counterfactual image models.

Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Exploring the Boundaries of GPT-4 in Radiology.

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

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing.

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Analysing the effectiveness of a generative model for semi-supervised medical image segmentation.

Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker

Proceedings of the Machine Learning for Health, 2022

Deep Structural Causal Shape Models.

Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing.

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

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Active label cleaning: Improving dataset quality under resource constraints.

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

CoRR, 2021

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs.

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

CoRR, 2021

2020

Deep Structural Causal Models for Tractable Counterfactual Inference.

Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty.

Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks.

Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Ben Glocker

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning.

Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker

J. Mach. Learn. Res., 2019

Causality matters in medical imaging.

Daniel Coelho de Castro, Ian Walker, Ben Glocker

CoRR, 2019

Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects.

Ben Glocker, Robert Robinson, Daniel Coelho de Castro, Qi Dou, Ender Konukoglu

CoRR, 2019

Domain Generalization via Model-Agnostic Learning of Semantic Features.

Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing.

Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker

Proceedings of the Information Processing in Medical Imaging, 2019

2018

Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model.

Daniel Coelho de Castro, Sebastian Nowozin

CoRR, 2018

Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning.

Jo Schlemper, Ozan Oktay, Wenjia Bai, Daniel Coelho de Castro, Jinming Duan, Chen Qin, Joseph V. Hajnal, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Bayesian Deep Learning for Accelerated MR Image Reconstruction.

Jo Schlemper, Daniel Coelho de Castro, Wenjia Bai, Chen Qin, Ozan Oktay, Jinming Duan, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert

Proceedings of the Machine Learning for Medical Image Reconstruction, 2018

Nonparametric Density Flows for MRI Intensity Normalisation.

Daniel Coelho de Castro, Ben Glocker

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Semi-Supervised Learning via Compact Latent Space Clustering.

Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori

Proceedings of the 35th International Conference on Machine Learning, 2018

From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data.

Daniel Coelho de Castro, Sebastian Nowozin

Proceedings of the Computer Vision - ECCV 2018, 2018