| 15-06-2018 |
Multifactorial segmentation of non-invasive light microscopy images using artificial intelligence
Non-invasive light microscopy is widely used in biology to inspect and investigate cells and tissues. Various contrasting techniques (e.g. Phase Contrast, DIC) are employed to enhance optical visualization. Unfortunately, this enhanced contrast returns highly complex interference patterns that complicate the analytical resolution of the current shape of the cell and thus images are subject to artefactual interpretations. To this end we are looking for talented students willing to learn and employ Artificial Intelligence and Deep Learning tools to generate a pipeline for multivariate segmentation. This project will be conducted at the Institute of Biological Engineering and Medical under the supervision of Prof. A. Ravasio and Prof. M. Rodriguez Fernandez, and in collaboration with the Department of Biological Engineering at MIT.
Keywords:
microscopy
artificial intelig
Prerequisites:
None.
Evaluation method: Nota 1-7, with 0/1 available vacants |
Mentor(s): Open in the plataform |