A framework for evaluating correspondence between brain images using anatomical fiducials. Issue 14 (7th June 2019)

• Record Type: Journal Article
• Authors: Lau, Jonathan C.; Parrent, Andrew G.; Demarco, John; Gupta, Geetika; Kai, Jason; Stanley, Olivia W.; Kuehn, Tristan; Park, Patrick J.; Ferko, Kayla; Khan, Ali R.; Peters, Terry M.
• Is Part Of: Human brain mapping. Volume 40:Issue 14(2019)
• Page Start: 4163
• Page End: 4179
• Publication Date: 2019-06-07
• Subjects: accuracy -- atlas -- brain -- deep brain stimulation -- education -- neuroanatomy -- nonlinear registration -- pallidum -- quality control -- striatum -- template -- thalamus; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.24693
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: 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.