output
20172023
most citedImproving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis

71 citations

6 papers

eess.IV2023★ 41 cited

CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images

Nicolás Gaggion, Candelaria Mosquera, Lucas Mansilla +4

The development of successful artificial intelligence models for chest X-ray analysis relies on large, diverse datasets with high-quality annotations. While several databases of ch…

eess.IV2022★ 71 cited

Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis

Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera +2

Anatomical segmentation is a fundamental task in medical image computing, generally tackled with fully convolutional neural networks which produce dense segmentation masks. These m…

eess.IV2020

Chest x-ray automated triage: a semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning architectures

Candelaria Mosquera, Facundo Nahuel Diaz, Fernando Binder +7

BACKGROUND AND OBJECTIVES: The multiple chest x-ray datasets released in the last years have ground-truth labels intended for different computer vision tasks, suggesting that perfo…

physics.bio-ph2019★ 18 cited

Inhibitory autapse mediates anticipated synchronization between coupled neurons

Marcel A. Pinto, Osvaldo A. Rosso, Fernanda S. Matias

Two identical autonomous dynamical systems unidirectionally coupled in a sender-receiver configuration can exhibit anticipated synchronization (AS) if the Receiver neuron (R) also…

stat.ME2017★ 18 cited

Confidence Intervals and Hypothesis Testing for the Permutation Entropy with an application to Epilepsy

Francisco Traversaro, Francisco Redelico

In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the a…

cs.HC2017★ 7 cited

Detecting Gamification in Breast Cancer Apps: an automatic methodology for screening purposes

Guido Giunti, Diego H Giunta, Santiago Hors-Fraile +2

Breast cancer is the most common cancer in women both in developed and developing countries. More than half of all cancer mobile application concern breast cancer. Gamification is…