Antonio Diaz-Parra

Orcid: 0000-0003-2469-8899

According to our database1, Antonio Diaz-Parra authored at least 9 papers between 2014 and 2023.

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

Timeline

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Bibliography

2023
MRI texture-based radiomics analysis for the identification of altered functional networks in alcoholic patients and animal models.
Comput. Medical Imaging Graph., March, 2023

2017
Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat.
NeuroImage, 2017

Brain functional connectivity alterations in a rat model of excessive alcohol drinking: A resting-state network analysis.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

Evaluating network brain connectivity in alcohol postdependent state using Network-Based Statistic.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

A fully automated method for segmentation and classification of local field potential recordings. Preliminary results.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

2015
Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression. Preliminary results.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

A fully automated level-set based segmentation method of thoracic and lumbar vertebral bodies in Computed Tomography images.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

2014
Fully automatic spinal canal segmentation for radiation therapy using a Gradient Vector Flow-based method on computed tomography images: A preliminary study.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

A fully automated method for spinal canal detection in computed tomography images.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014


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