title: Atlas-based indexing of brain sections via 2-D to 3-D image registration.
abstract: A 2-D to 3-D nonlinear intensity-based registration method is proposed in which the alignment of histological brain sections with a volumetric brain atlas is performed. First, sparsely cut brain sections were linearly matched with an oblique slice automatically extracted from the atlas. Second, a planar-to-curved surface alignment was employed in order to match each section with its corresponding image overlaid on a curved-surface within the atlas. For the latter, a PDE-based registration technique was developed that is driven by a local normalized-mutual-information similarity measure. We demonstrate the method and evaluate its performance with simulated and real data experiments. An atlas-guided segmentation of mouse brains' hippocampal complex, retrieved from the Mouse Brain Library (MBL) database, is demonstrated with the proposed algorithm.
authors.affiliation: PVI Virtual Media Services LLC, 15 Princess Road, Lawrenceville, NJ 08648, USA. sgefen@pvi.tv
authors.forename: Smadar
authors.initials: S
authors.lastname: Gefen
authors.forename: Nahum
authors.initials: N
authors.lastname: Kiryati
authors.forename: Jonathan
authors.initials: J
authors.lastname: Nissanov
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods*; D000818:Animals; D001921:Brain / Q000166:cytology*; D005240:Feasibility Studies; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D051379:Mice; D010363:Pattern Recognition, Automated / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique