title: Statistical atlas construction via weighted functional boxplots.
abstract: Atlas-building from population data is widely used in medical imaging. However, the emphasis of atlas-building approaches is typically to estimate a spatial alignment to compute a mean/median shape or image based on population data. In this work, we focus on the statistical characterization of the population data, once spatial alignment has been achieved. We introduce and propose the use of the weighted functional boxplot. This allows the generalization of concepts such as the median, percentiles, or outliers to spaces where the data objects are functions, shapes, or images, and allows spatio-temporal atlas-building based on kernel regression. In our experiments, we demonstrate the utility of the approach to construct statistical atlases for pediatric upper airways and corpora callosa revealing their growth patterns. We also define a score system based on the pediatric airway atlas to quantitatively measure the severity of subglottic stenosis (SGS) in the airway. This scoring allows the classification of pre- and post-surgery SGS subjects and radiographically normal controls. Experimental results show the utility of atlas information to assess the effect of airway surgery in children.
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA. Electronic address: yihong@cs.unc.edu.
authors.forename: Yi
authors.initials: Y
authors.lastname: Hong
authors.affiliation: Kitware, Inc., Carrboro, NC, USA.
authors.forename: Brad
authors.initials: B
authors.lastname: Davis
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA.
authors.forename: J S
authors.initials: JS
authors.lastname: Marron
authors.affiliation: Department of Computer Science, University of Salzburg, Austria.
authors.forename: Roland
authors.initials: R
authors.lastname: Kwitt
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA.
authors.forename: Nikhil
authors.initials: N
authors.lastname: Singh
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA.
authors.forename: Julia S
authors.initials: JS
authors.lastname: Kimbell
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Pitkin
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Superfine
authors.affiliation: Indiana University School of Medicine, Indianapolis, IN, USA.
authors.forename: Stephanie D
authors.initials: SD
authors.lastname: Davis
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA.
authors.forename: Carlton J
authors.initials: CJ
authors.lastname: Zdanski
authors.affiliation: University of North Carolina (UNC) at Chapel Hill, NC, USA; Biomedical Research Imaging Center, UNC-Chapel Hill, NC, USA.
authors.forename: Marc
authors.initials: M
authors.lastname: Niethammer
mesh_terms: D001271:Atlases as Topic; D001921:Brain / Q000033:anatomy & histology; D003337:Corpus Callosum / Q000033:anatomy & histology; D006801:Humans; D007223:Infant; D015233:Models, Statistical; D012137:Respiratory System / Q000033:anatomy & histology; D013223:Statistics as Topic
keywords: Kernel regression; Pediatric upper airways; Statistical atlas-building; Weighted functional boxplots
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