| 30-03-2021 |
Deep learning for inverse problems in Astronomy and Medical Imaging
In Astronomical Instrumentation and Biomedical Imaging, we find challenges with great similarities. Discoveries in one area have often helped to improve reconstruction methods and algorithms in the other, and vice versa. Today, an important challenge is to integrate deep-learning methods to improve and automate image reconstruction methods (inverse problems), in particular for adaptive optics in astronomy, and for obtaining quantitative information in cardiac MRI (magnetic resonance imaging). In this work, we propose to carry out a bibliographic study to analyse and compare the problems addressed in these two areas and deep-learning methods proposed to date in these two fields.
Prerequisites:
None.
Evaluation method: Nota 1-7, with 0/1 available vacants |
Mentor(s): Open in the plataform |
| 24-07-2020 |
Study of tomographic adaptive optics reconstructors
Prerequisites:
None.
Evaluation method: Nota 1-7, with 0/1 available vacants |
Mentor(s): Open in the plataform |