Álvar Legaz-Aparicio

Orcid: 0000-0002-6450-9653

According to our database1, Álvar Legaz-Aparicio authored at least 12 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A hybrid framework for efficient and accurate orientation estimation based on single and multiple orientation vector fields.
Expert Syst. Appl., November, 2023

2020
A rolling horizon simulation approach for managing demand with lead time variability.
Int. J. Prod. Res., 2020

2018
Multiscale estimation of multiple orientations based on morphological directional openings.
Signal Image Video Process., 2018

Adaptive morphological filters based on a multiple orientation vector field dependent on image local features.
J. Comput. Appl. Math., 2018

Noise robust and rotation invariant framework for texture analysis and classification.
Appl. Math. Comput., 2018

2017
Retinal network characterization through fundus image processing: Significant point identification on vessel centerline.
Signal Process. Image Commun., 2017

Efficient Variational Approach to Multimodal Registration of Anatomical and Functional Intra-Patient Tumorous Brain Data.
Int. J. Neural Syst., 2017

2015
Multimodal 3D Registration of Anatomic (MRI) and Functional (fMRI and PET) Intra-patient Images of the Brain.
Proceedings of the Artificial Computation in Biology and Medicine, 2015

Dynamic Modelling of the Whole Heart Based on a Frequency Formulation and Implementation of Parametric Deformable Models.
Proceedings of the Artificial Computation in Biology and Medicine, 2015

Using Machine Learning Techniques for the Automatic Detection of Arterial Wall Layers in Carotid Ultrasounds.
Proceedings of the Ambient Intelligence - Software and Applications, 2015

Determination of Bifurcation Angles of the Retinal Vascular Tree through Multiple Orientation Estimation based on Regularized Morphological Openings.
Proceedings of the BIOSIGNALS 2015, 2015

2013
Comparison of Finite Difference and B-Spline Deformable Models in Characterization of 3D Data.
Proceedings of the Natural and Artificial Computation in Engineering and Medical Applications, 2013


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