PT  - JOURNAL ARTICLE
AU  - Jonathan C. Lau
AU  - Andrew G. Parrent
AU  - John Demarco
AU  - Geetika Gupta
AU  - Patrick J. Park
AU  - Kayla Ferko
AU  - Ali R. Khan
AU  - Terry M. Peters
TI  - A framework for evaluating correspondence between brain images using anatomical fiducials
AID  - 10.1101/460675
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 460675
4099  - http://biorxiv.org/content/early/2018/11/03/460675.short
4100  - http://biorxiv.org/content/early/2018/11/03/460675.full
AB  - Accurate spatial correspondence between template and subject images is a crucial step in neuroimaging studies and clinical applications like stereotactic neurosurgery. In the absence of a robust quantitative approach, we sought to propose and validate a set of point landmarks, anatomical fiducials (AFIDs), that could be quickly, accurately, and reliably placed on magnetic resonance images of the human brain. Using several publicly available brain templates and individual participant datasets, novice users could be trained to place a set of 32 AFIDs with millimetric accuracy. Furthermore, the utility of the AFIDs protocol is demonstrated for evaluating subject-to-template and template-to-template registration. Specifically, we found that commonly used voxel overlap metrics were relatively insensitive to focal misregistrations compared to AFID point-based measures. Our entire protocol and study framework leverages open resources and tools, and has been developed with full transparency in mind so that others may freely use, adopt, and modify. This protocol holds value for a broad number of applications including alignment of brain images and teaching neuroanatomy.