title: Three-dimensional reconstruction and quantitative analysis of the brain stem nuclei based on fast centroid auto-registration.
abstract: This paper introduces a three-dimensional (3D) reconstruction algorithm of the brain stem nuclei based on fast centroid auto-registration. The research is based on methods and theories of computer stereo vision, and by image information processing three-point pattern local search, registration and auto-tracing for the centroids of the brain stem nuclei were accomplished. We adopt two-peak threshold, edge detection and grayscale image enhancement to extract contours of the nuclei's structures. The experimental results obtain the spatial structure information and 3D image of the brain stem nuclei, show spatial relationship between 14 pairs of nuclei, and quantitate morphological parameters of each type of nuclei's 3D structure. This work is significant to neuroanatomy research and clinic applications. Furthermore, a software system named BRAIN.HUK is established.
authors.affiliation: Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Yi-Chen
authors.initials: YC
authors.lastname: Chen
authors.forename: Kuang-Hu
authors.initials: KH
authors.lastname: Hu
authors.forename: Fang-Zhen
authors.initials: FZ
authors.lastname: Li
authors.forename: Wan-Fang
authors.initials: WF
authors.lastname: Su
authors.forename: Bao-Lin
authors.initials: BL
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D001933:Brain Stem / Q000166:cytology*; D005260:Female; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D009415:Nerve Net / Q000166:cytology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D051381:Rats; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013382:Subtraction Technique