Construction of an MRI 3D high resolution sheep brain template

• Published in: Magnetic resonance imaging Vol. 33; no. 10; pp. 1329 - 1337
• Main Authors: Ella, Arsène, Keller, Matthieu
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.12.2015; Elsevier
• Subjects: Animals; Brain - anatomy & histology; Brain Mapping - methods; Image Processing, Computer-Assisted - methods; Image registration; Imaging, Three-Dimensional - methods; In-vivo sheep brain; Life Sciences; Magnetic Resonance Imaging - methods; MRI; Other; Prior probability map; Radiology; Segmentation; Sheep; Template; Image registration; Segmentation; MRI; In-vivo sheep brain; Template; Prior probability map; template; prior probability map; segmentation; in-vivo sheep brain; image registration; mri
• ISSN: 0730-725X; 1873-5894
• DOI: 10.1016/j.mri.2015.09.001

Sheep is a developing animal model used in the field of neurosciences for the study of many behavioral, physiological or pathophysiological mechanisms, including for example, the central control of social behavior, brain injury or neurodegenerative diseases. However, sheep remains an orphan species in the field of magnetic resonance imaging (MRI). Therefore, a mean image (template), resulting of registrations of multiple subject images is needed and currently does not exist. In this study, we: i) computed multimodal high resolution 3D in-vivo sheep brain templates of T1 weighted (T1W) and T2W images, ii) computed gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) prior probability maps using linear and optimized non-linear registrations iii) used prior probability maps to perform the segmentation of a single brain tissues. Computed multimodal sheep brain templates showed to preserve and underline all brain patterns of a single T1W or T2W image, and prior probability maps allowed to improve the segmentation of brain tissues. Finally, we demonstrated that these templates and prior probability maps were able to be portable in other publicly available imaging software and could be used as standardized spaces for multi-institution neuroimaging studies or other neuroscience methods.