5 datasets found

Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images.

The Harvard Whole Brain Atlas dataset contains MRI and PET images of patients with various brain conditions.

The sulcal and gyral curve extraction method (TRACE) dataset contains cortical sulcal curves extracted from T1-weighted MRI of 444 subjects.

The dataset used in the paper is a subset of the Human Connectome Project dataset, containing functional connectivity MRI scans from 865 subjects.

Modeling the behavior of coupled networks is challenging due to their intricate dynamics. For example in neuroscience, it is of critical importance to understand the...