Fernando Pérez-García
Orcid: 0000-0001-9090-3024
According to our database1,
Fernando Pérez-García authored at least 95 papers
between 2017 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
CoRR, November, 2025
CoRR, October, 2025
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology.
ACM Trans. Comput. Hum. Interact., August, 2025
Nat. Mac. Intell., 2025
2024
Medical Image Anal., 2024
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology.
CoRR, 2024
CoRR, 2024
MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models.
Proceedings of the Machine Learning for Health, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology.
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024
MAIRA at RRG24: A specialised large multimodal model for radiology report generation.
Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, 2024
2023
Trans. Assoc. Comput. Linguistics, 2023
CoRR, 2023
Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query.
CoRR, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
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.
Frontiers Neuroinformatics, August, 2022
CoRR, 2022
2021
Machine Learning for Localizing Epileptogenic-Zone in the Temporal Lobe: Quantifying the Value of Multimodal Clinical-Semiology and Imaging Concordance.
Frontiers Digit. Health, 2021
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning.
Comput. Methods Programs Biomed., 2021
A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections.
Int. J. Comput. Assist. Radiol. Surg., 2021
A generative model of hyperelastic strain energy density functions for multiple tissue brain deformation.
Int. J. Comput. Assist. Radiol. Surg., 2021
Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures.
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.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
2018
2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.1.
Dataset, May, 2017