Fernando Pérez-García

According to our database, Fernando Pérez-García authored at least 16 papers between 2020 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

Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query.

Ho Hin Lee, Alberto Santamaría-Pang, Jameson Merkow, Ozan Oktay, Fernando Pérez-García, Javier Alvarez-Valle, Ivan Tarapov

CoRR, 2023

Compositional Zero-Shot Domain Transfer with Text-to-Text Models.

Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland

CoRR, 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

Software tool for visualization of a probabilistic map of the epileptogenic zone from seizure semiologies.

Fernando Pérez-García, Ali Alim-Marvasti, Gloria Romagnoli, Matthew J. Clarkson, Rachel Sparks, John S. Duncan, Sébastien Ourselin

Frontiers Neuroinformatics, August, 2022

MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images.

Andres Diaz-Pinto, Sachidanand Alle, Alvin Ihsani, Muhammad Asad, Vishwesh Nath, Fernando Pérez-García, Pritesh Mehta, Wenqi Li, Holger R. Roth, Tom Vercauteren, Daguang Xu, Prerna Dogra, Sébastien Ourselin, Andrew Feng, M. Jorge Cardoso

CoRR, 2022

2021

Machine Learning for Localizing Epileptogenic-Zone in the Temporal Lobe: Quantifying the Value of Multimodal Clinical-Semiology and Imaging Concordance.

Ali Alim-Marvasti, Fernando Pérez-García, Karan Dahele, Gloria Romagnoli, Beate Diehl, Rachel Sparks, Sébastien Ourselin, Matthew J. Clarkson, John S. Duncan

Frontiers Digit. Health, 2021

TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning.

Fernando Pérez-García, Rachel Sparks, Sébastien Ourselin

Comput. Methods Programs Biomed., 2021

A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections.

Fernando Pérez-García, Reuben Dorent, Michele Rizzi, Francesco Cardinale, Valerio Frazzini, Vincent Navarro, Caroline Essert, Irène Ollivier, Tom Vercauteren, Rachel Sparks, John S. Duncan, Sébastien Ourselin

Int. J. Comput. Assist. Radiol. Surg., 2021

A generative model of hyperelastic strain energy density functions for multiple tissue brain deformation.

Alejandro Granados, Fernando Pérez-García, Martin Schweiger, Vejay Vakharia, Sjoerd B. Vos, Anna Miserocchi, Andrew W. McEvoy, John S. Duncan, Rachel Sparks, Sébastien Ourselin

Int. J. Comput. Assist. Radiol. Surg., 2021

Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures.

Fernando Pérez-García, Catherine J. Scott, Rachel Sparks, Beate Diehl, Sébastien Ourselin

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020

Simulation of Brain Resection for Cavity Segmentation Using Self-supervised and Semi-supervised Learning.

Fernando Pérez-García, Roman Rodionov, Ali Alim-Marvasti, Rachel Sparks, John S. Duncan, Sébastien Ourselin

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