Deep learning approaches for MRI-based labelling of neuroanatomical structures following epilepsy surgery
The aim of this project is to train a deep learning model to label resected brain regions and other related neuroanatomical structures using a large dataset (n = 697) of postsurgical MRI scans.
This project would be well suited to students with an interest in data science and artificial intelligence techniques.
Aim
- Train a deep learning model to label resected brain regions of postsurgical MRI scans.
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