Saliency-based Cerebellar Parcellation

doi:doi:10.57702/gywmyqn1

Saliency-based Cerebellar Parcellation

The Human Connectome Project minimally preprocessed young adult dataset imaging data and associated NIH toolbox measures are used to train a deep learning model to predict individual functional performance measures from structural features.

BibTex:

@dataset{Ari_Tchetchenian_and_Leo_Zekelman_and_Yuqian_Chen_and_Jarrett_Rushmore_and_Fan_Zhang_and_Edward_H_Yeterian_and_Nikos_Makris_and_Yogesh_Rathi_and_Erik_Meijering_and_Yang_Song_2024,
    abstract = {The Human Connectome Project minimally preprocessed young adult dataset imaging data and associated NIH toolbox measures are used to train a deep learning model to predict individual functional performance measures from structural features.},
    author = {Ari Tchetchenian and Leo Zekelman and Yuqian Chen and Jarrett Rushmore and Fan Zhang and Edward H. Yeterian and Nikos Makris and Yogesh Rathi and Erik Meijering and Yang Song},
    doi = {10.57702/gywmyqn1},
    institution = {No Organization},
    keyword = {'cerebellar pathways', 'diffusion MRI', 'functional performance measures', 'white matter tracts'},
    month = {dec},
    publisher = {TIB},
    title = {Saliency-based Cerebellar Parcellation},
    url = {https://service.tib.eu/ldmservice/dataset/saliency-based-cerebellar-parcellation},
    year = {2024}
}