title: Probabilistic liver atlas construction.
abstract: BACKGROUND
  Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location.
  
  
  RESULTS
  A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step.
  
  
  CONCLUSIONS
  We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.
authors.affiliation: Department of Informatics, School of Engineering, University of Valencia, Avda. de la Universidad, 46100, Burjasot, Spain.
authors.forename: Esther
authors.initials: E
authors.lastname: Dura
authors.affiliation: Department of Informatics, School of Engineering, University of Valencia, Avda. de la Universidad, 46100, Burjasot, Spain.
authors.forename: Juan
authors.initials: J
authors.lastname: Domingo
authors.affiliation: Department of Statistics and Operations Research, University of Valencia, Avda. Vicent Andrés Estellés, 1, 46100, Burjasot, Spain. Guillermo.Ayala@uv.es.
authors.forename: Guillermo
authors.identifier: http://orcid.org/0000-0002-6231-2865
authors.initials: G
authors.lastname: Ayala
authors.affiliation: Universitary and Politechnic Hospital La Fe, Valencia, Spain.
authors.forename: Luis
authors.initials: L
authors.lastname: Marti-Bonmati
authors.affiliation: Department of Computer Engineering, Akdeniz University, Antalya, Turkey.
authors.forename: E
authors.initials: E
authors.lastname: Goceri
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008099:Liver / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011336:Probability; D013223:Statistics as Topic / Q000379:methods*
keywords: Anatomical atlas; Atlas variability; Coregistration method; Generalized linear model; Probabilistic atlas