Nicolás Gaggion

17 papers Journal 13Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mask-HybridGNet: Graph-based segmentation with emergent anatomical correspondence from pixel-level supervision. CoRR Nicolás Gaggion, María-Jesus Ledesma-Carbayo, Stergios Christodoulidis, Maria Vakalopoulou, Enzo Ferrante
2025	J	`jnl`	CheXmask-U: Quantifying uncertainty in landmark-based anatomical segmentation for X-ray images. CoRR Matias Cosarinsky, Nicolás Gaggion, Rodrigo Echeveste, Enzo Ferrante
2025	J	`jnl`	ChronoRoot 2.0: An Open AI-Powered Platform for 2D Temporal Plant Phenotyping. CoRR 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
2025	J	`jnl`	In-Context Reverse Classification Accuracy: Efficient Estimation of Segmentation Quality without Ground-Truth. CoRR Matias Cosarinsky, Ramiro Billot, Lucas Mansilla, Gabriel Gimenez, Nicolás Gaggion, Guanghui Fu, Enzo Ferrante
2025	J	`jnl`	Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI. Medical Image Anal. Nicolás Gaggion, Benjamin A. Matheson, Yan Xia, Rodrigo Bonazzola, Nishant Ravikumar, Zeike A. Taylor, Diego H. Milone, Alejandro F. Frangi, Enzo Ferrante
2024	—	`conf`	Fitting Skeletal Models via Graph-Based Learning. ISBI Nicolás Gaggion, Enzo Ferrante, Beatriz Paniagua, Jared Vicory
2024	J	`jnl`	Fitting Skeletal Models via Graph-based Learning. CoRR Nicolás Gaggion, Enzo Ferrante, Beatriz Paniagua, Jared Vicory
2023	J	`jnl`	CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images. CoRR Nicolás Gaggion, Candelaria Mosquera, Lucas Mansilla, Martina Aineseder, Diego H. Milone, Enzo Ferrante
2023	J	`jnl`	Improving Anatomical Plausibility in Medical Image Segmentation via Hybrid Graph Neural Networks: Applications to Chest X-Ray Analysis. IEEE Trans. Medical Imaging Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante
2023	—	`conf`	Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models. ISBI Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante
2023	J	`jnl`	Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI. CoRR Nicolás Gaggion, Benjamin A. Matheson, Yan Xia, Rodrigo Bonazzola, Nishant Ravikumar, Zeike A. Taylor, Diego H. Milone, Alejandro F. Frangi, Enzo Ferrante
2023	—	`conf`	Unsupervised Bias Discovery in Medical Image Segmentation. CLIP/FAIMI/EPIMI@MICCAI Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante
2023	J	`jnl`	Unsupervised bias discovery in medical image segmentation. CoRR Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante
2022	J	`jnl`	Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis. CoRR Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante
2022	J	`jnl`	Multi-center anatomical segmentation with heterogeneous labels via landmark-based models. CoRR Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante
2021	—	`conf`	Hybrid Graph Convolutional Neural Networks for Landmark-Based Anatomical Segmentation. MICCAI (1) Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante
2021	J	`jnl`	Hybrid graph convolutional neural networks for landmark-based anatomical segmentation. CoRR Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante