Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults.
In model-based segmentation, automated region identification is achieved via registration of novel data to a pre-determined model. The desired structure is typically generated via manual tracing within this model. When model-based segmentation is applied to human cortical data, problems arise if left-right comparisons are desired. The asymmetry of the human cortex requires that both left and right models of a structure be composed in order to effectively segment the desired structures. Paradoxically, defining a model in both hemi-spheres carries a likelihood of introducing bias to one of the structures. This paper describes a novel technique for creating a symmetric average model in which both hemispheres are equally represented and thus left-right comparison is possible. This work is an extension of that proposed by Guimond et al. Hippocampal segmentation is used as a test-case in a cohort of 118 normal eld-erly subjects and results are compared with expert manual tracing.
Grabner
Günther
G
McConnell Brain Imaging Centre, Montreal Neurological Institute, Quebec, Canada.
Janke
Andrew L
AL
Budge
Marc M
MM
Smith
David
D
Pruessner
Jens
J
Collins
D Louis
DL
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000716:Anatomy, Artistic / Q000379:methods; D001185:Artificial Intelligence; D003198:Computer Simulation; D006624:Hippocampus / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008488:Medical Illustration; D008875:Middle Aged; D008959:Models, Neurological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity