Angélica Atehortúa

Orcid: 0000-0002-6192-1757

Affiliations:
  • National University of Colombia, Bogotá, Colombia


According to our database1, Angélica Atehortúa authored at least 12 papers between 2013 and 2023.

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Bibliography

2023
Cardiometabolic risk estimation using exposome data and machine learning.
Int. J. Medical Informatics, November, 2023

2022
Characterization of motion patterns by a spatio-temporal saliency descriptor in cardiac cine MRI.
Comput. Methods Programs Biomed., 2022

2021
Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data.
IEEE J. Biomed. Health Informatics, 2021

2020
Fusion of 3D real-time echocardiography and cine MRI using a saliency analysis.
Int. J. Comput. Assist. Radiol. Surg., 2020

2018
Ocular Control Characterization of Motor Disabilities: The Cerebral Palsy Case.
Proceedings of the Processing and Analysis of Biomedical Information, 2018

Automatic Left Ventricle Quantification in Cardiac MRI via Hierarchical Refinement of High-Level Features by a Salient Perceptual Grouping Model.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018

2017
Quantifying gait patterns in Parkinson's disease.
Proceedings of the 13th International Symposium on Medical Information Processing and Analysis, 2017

Quantifying stimulus-response rehabilitation protocols by auditory feedback in Parkinson's disease gait pattern.
Proceedings of the 13th International Symposium on Medical Information Processing and Analysis, 2017

Cerebral palsy characterization by estimating ocular motion.
Proceedings of the 13th International Symposium on Medical Information Processing and Analysis, 2017

Fusion of 4D echocardiography and cine cardiac magnetic resonance volumes using a salient spatio-temporal analysis.
Proceedings of the 13th International Symposium on Medical Information Processing and Analysis, 2017

2016
Automatic segmentation of 4D cardiac MR images for extraction of ventricular chambers using a spatio-temporal approach.
Proceedings of the Medical Imaging 2016: Image Processing, 2016

2013
A Novel Right Ventricle Segmentation Approach from Local Spatio-temporal MRI Information.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2013


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