The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of anatomical protocols for the delineation of 21 individual subcortical structures. These protocols are augmented with three example MRI datasets combined with their manual delineations. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients which showed that manual parcellations created using these protocols can provide high quality training data for automated algorithms. The protocols can be applied to create high quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community.
This work was financially supported by NWO/STW #14017 (AA, MJM, BUF), NWO-Vici and ERC proof of concept (BUF) grants.
Research priority area
- Brain & Cognition