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ORCIDAriel Hernán Curiale
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2020 – today
- 2024
[c5]Ariel Hernán Curiale
, Raúl San José Estépar:
Lobar Lung Density Embeddings with a Transformer Encoder (LobTe) to Predict Emphysema Progression in COPD. MICCAI (1) 2024: 557-566- 2022
- [i5]Ariel Hernán Curiale, Facundo Cabrera, Pablo Jimenez, Jorgelina Medus, Germán Mato, Matías E. Calandrelli:
Detection of Fibrosis in Cine Magnetic Resonance Images Using Artificial Intelligence Techniques. CoRR abs/2206.01745 (2022) - [i4]Ariel Hernán Curiale, Matías E. Calandrelli, Lucca Dellazoppa, Mariano Trevisan, Jorge Luis Bocián, Juan Pablo Bonifacio, Germán Mato:
Automatic Quantification of Volumes and Biventricular Function in Cardiac Resonance. Validation of a New Artificial Intelligence Approach. CoRR abs/2206.01746 (2022) - 2021
- [j5]Ariel Hernán Curiale, Agustín Bernardo, Rodrigo Cárdenas, Germán Mato:
CardIAc: an open-source application for myocardial strain analysis. Int. J. Comput. Assist. Radiol. Surg. 16(1): 65-79 (2021) - [c4]Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel Hernán Curiale, Rubén San José Estépar, Raúl San José Estépar, Marc Niethammer:
Accurate Point Cloud Registration with Robust Optimal Transport. NeurIPS 2021: 5373-5389 - [i3]Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel Hernán Curiale, Rubén San José Estépar, Raúl San José Estépar, Marc Niethammer:
Accurate Point Cloud Registration with Robust Optimal Transport. CoRR abs/2111.00648 (2021)
2010 – 2019
- 2019
- [j4]Ariel Hernán Curiale, Flavio D. Colavecchia, Germán Mato:
Automatic quantification of the LV function and mass: A deep learning approach for cardiovascular MRI. Comput. Methods Programs Biomed. 169: 37-50 (2019) - 2018
- [i2]Ariel Hernán Curiale, Flavio D. Colavecchia, Germán Mato:
Automatic quantification of the LV function and mass: a deep learning approach for cardiovascular MRI. CoRR abs/1812.06061 (2018) - 2017
- [c3]Ariel Hernán Curiale, Flavio D. Colavecchia, Pablo Kaluza, Roberto A. Isoardi, Germán Mato:
Automatic myocardial segmentation by using a deep learning network in cardiac MRI. CLEI 2017: 1-6 - [i1]Ariel Hernán Curiale, Flavio D. Colavecchia, Pablo Kaluza, Roberto A. Isoardi, Germán Mato:
Automatic Myocardial Segmentation by Using A Deep Learning Network in Cardiac MRI. CoRR abs/1708.07452 (2017) - 2016
- [j3]Ariel Hernán Curiale, Gonzalo Vegas-Sánchez-Ferrero, Santiago Aja-Fernández:
Influence of ultrasound speckle tracking strategies for motion and strain estimation. Medical Image Anal. 32: 184-200 (2016) - 2015
- [j2]Santiago Aja-Fernández, Ariel Hernán Curiale, Gonzalo Vegas-Sánchez-Ferrero:
A local fuzzy thresholding methodology for multiregion image segmentation. Knowl. Based Syst. 83: 1-12 (2015) - [j1]Ariel Hernán Curiale, Gonzalo Vegas-Sánchez-Ferrero, Johan G. Bosch, Santiago Aja-Fernández:
A maximum likelihood approach to diffeomorphic speckle tracking for 3D strain estimation in echocardiography. Medical Image Anal. 24(1): 90-105 (2015) - 2013
- [c2]Ariel Hernán Curiale, Gonzalo Vegas-Sánchez-Ferrero, Santiago Aja-Fernández:
Speckle Tracking in Interpolated Echocardiography to Estimate Heart Motion. FIMH 2013: 325-333 - [c1]Ariel Hernán Curiale, Gonzalo Vegas-Sánchez-Ferrero, T. Perez-Sanz, Santiago Aja-Fernández:
Strain rate tensor estimation from echocardiography for quantitative assessment of functional mitral regurgitation. ISBI 2013: 788-791
Coauthor Index
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