Fernando Pérez-García

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

May 09, 2023
Ho Hin Lee, Alberto Santamaria-Pang, Jameson Merkow, Ozan Oktay, Fernando Pérez-García, Javier Alvarez-Valle, Ivan Tarapov

Figure 2 for Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query

Figure 3 for Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query

Figure 4 for Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query

Access Paper or Ask Questions

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

Mar 23, 2023
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland

Figure 2 for Compositional Zero-Shot Domain Transfer with Text-to-Text Models

Figure 3 for Compositional Zero-Shot Domain Transfer with Text-to-Text Models

Figure 4 for Compositional Zero-Shot Domain Transfer with Text-to-Text Models

* Accepted at TACL, pre-MIT Press publication version. 16 pages, 4 figures

Access Paper or Ask Questions

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

Mar 23, 2022
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, Sebastien Ourselin, Andrew Feng, M. Jorge Cardoso

Figure 2 for MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images

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

Figure 4 for MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images

Access Paper or Ask Questions

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

Jun 22, 2021
Fernando Pérez-García, Catherine Scott, Rachel Sparks, Beate Diehl, Sébastien Ourselin

Figure 2 for Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures

Figure 3 for Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures

* Accepted at the 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021)

Access Paper or Ask Questions

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

May 24, 2021
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

Figure 2 for A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

Figure 3 for A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

Figure 4 for A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

* To be published in the International Journal of Computer Assisted Radiology and Surgery (IJCARS) - Special issue MICCAI 2020

Access Paper or Ask Questions

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

Jun 28, 2020
Fernando Pérez-García, Roman Rodionov, Ali Alim-Marvasti, Rachel Sparks, John S. Duncan, Sébastien Ourselin

Figure 2 for Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised Learning

Figure 3 for Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised Learning

Figure 4 for Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised Learning

* 13 pages, 6 figures, accepted at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020

Access Paper or Ask Questions

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

Mar 09, 2020
Fernando Pérez-García, Rachel Sparks, Sebastien Ourselin

Figure 1 for TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning

Figure 2 for TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning

Figure 3 for TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning

Figure 4 for TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning

* 14 pages, 4 figures

Access Paper or Ask Questions