果冻传媒

The first application explored by Seb Harrevelt as part of his PhD research uses a deep learning approach to correct RF field inhomogeneities in 7T prostate imaging, outperforming the traditional N4-algorithm.

The second application focused on developing a field strength-agnostic cardiac segmentation network using different augmentation methods to generate training data.

For the third study, Harrevelt sought to reconstruct 7T cardiac images from undersampled data by fine-tuning pre-trained networks showing that minimal additional 7T data enhances performance.

Lastly, as part of the Dutch National 14T MRI Initiative, Harrevelt and his colleagues compared multiple potential RF antenna array designs for 14T imaging by simulating their RF field and the corresponding distribution of power deposition.

Title of PhD thesis: . Supervisors: Josien Plum and Alexander Raaijmakers.