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ORCIDNicolás Gaggion
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2020 – today
- 2025
[j2]Nicolás Gaggion, Benjamin A. Matheson
, Yan Xia, Rodrigo Bonazzola, Nishant Ravikumar, Zeike A. Taylor, Diego H. Milone, Alejandro F. Frangi, Enzo Ferrante:
Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI. Medical Image Anal. 104: 103630 (2025)- [i10]Matias Cosarinsky, Ramiro Billot, Lucas Mansilla, Gabriel Gimenez, Nicolás Gaggion, Guanghui Fu, Enzo Ferrante:
In-Context Reverse Classification Accuracy: Efficient Estimation of Segmentation Quality without Ground-Truth. CoRR abs/2503.04522 (2025) - [i9]Nicolás Gaggion, Rodrigo Bonazzola, María Florencia Legascue, María Florencia Mammarella, Florencia Sol Rodriguez, Federico Emanuel Aballay, Florencia Belén Catulo, Andana Barrios, Franco Accavallo, Santiago Nahuel Villarreal, Martin Crespi, Martiniano María Ricardi, Ezequiel Petrillo, Thomas Blein, Federico Ariel, Enzo Ferrante:
ChronoRoot 2.0: An Open AI-Powered Platform for 2D Temporal Plant Phenotyping. CoRR abs/2504.14736 (2025) - [i8]Matias Cosarinsky, Nicolás Gaggion, Rodrigo Echeveste, Enzo Ferrante:
CheXmask-U: Quantifying uncertainty in landmark-based anatomical segmentation for X-ray images. CoRR abs/2512.10715 (2025) - 2024
- [c4]Nicolás Gaggion, Enzo Ferrante, Beatriz Paniagua, Jared Vicory:
Fitting Skeletal Models via Graph-Based Learning. ISBI 2024: 1-4 - [i7]Nicolás Gaggion, Enzo Ferrante, Beatriz Paniagua, Jared Vicory:
Fitting Skeletal Models via Graph-based Learning. CoRR abs/2409.05311 (2024) - 2023
- [j1]Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante:
Improving Anatomical Plausibility in Medical Image Segmentation via Hybrid Graph Neural Networks: Applications to Chest X-Ray Analysis. IEEE Trans. Medical Imaging 42(2): 546-556 (2023) - [c3]Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised Bias Discovery in Medical Image Segmentation. CLIP/FAIMI/EPIMI@MICCAI 2023: 266-275 - [c2]Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante:
Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models. ISBI 2023: 1-5 - [i6]Nicolás Gaggion, Candelaria Mosquera, Lucas Mansilla, Martina Aineseder, Diego H. Milone, Enzo Ferrante:
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images. CoRR abs/2307.03293 (2023) - [i5]Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised bias discovery in medical image segmentation. CoRR abs/2309.00451 (2023) - [i4]Nicolás Gaggion, Benjamin A. Matheson, Yan Xia, Rodrigo Bonazzola, Nishant Ravikumar, Zeike A. Taylor, Diego H. Milone, Alejandro F. Frangi, Enzo Ferrante:
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI. CoRR abs/2311.13706 (2023) - 2022
- [i3]Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante:
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis. CoRR abs/2203.10977 (2022) - [i2]Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante:
Multi-center anatomical segmentation with heterogeneous labels via landmark-based models. CoRR abs/2211.07395 (2022) - 2021
- [c1]Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid Graph Convolutional Neural Networks for Landmark-Based Anatomical Segmentation. MICCAI (1) 2021: 600-610 - [i1]Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid graph convolutional neural networks for landmark-based anatomical segmentation. CoRR abs/2106.09832 (2021)
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