title: An image database of Drosophila melanogaster wings for phenomic and biometric analysis.
abstract: Extracting important descriptors and features from images of biological specimens is an ongoing challenge. Features are often defined using landmarks and semi-landmarks that are determined a priori based on criteria such as homology or some other measure of biological significance. An alternative, widely used strategy uses computational pattern recognition, in which features are acquired from the image de novo. Subsets of these features are then selected based on objective criteria. Computational pattern recognition has been extensively developed primarily for the classification of samples into groups, whereas landmark methods have been broadly applied to biological inference.
  
  
  
  To compare these approaches and to provide a general community resource, we have constructed an image database of Drosophila melanogaster wings - individually identifiable and organized by sex, genotype and replicate imaging system - for the development and testing of measurement and classification tools for biological images. We have used this database to evaluate the relative performance of current classification strategies. Several supervised parametric and nonparametric machine learning algorithms were used on principal components extracted from geometric morphometric shape data (landmarks and semi-landmarks). For comparison, we also classified phenotypes based on de novo features extracted from wing images using several computer vision and pattern recognition methods as implemented in the Bioimage Classification and Annotation Tool (BioCAT).
  
  
  
  Because we were able to thoroughly evaluate these strategies using the publicly available Drosophila wing database, we believe that this resource will facilitate the development and testing of new tools for the measurement and classification of complex biological phenotypes.
authors.affiliation: Genetics Graduate Program, Michigan State University, East Lansing, MI, 48824, USA.|BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, 48824, USA.
authors.forename: Anne
authors.initials: A
authors.lastname: Sonnenschein
authors.affiliation: Department of Integrative Biology, Michigan State University, East Lansing, MI, 48824, USA.
authors.forename: David
authors.initials: D
authors.lastname: VanderZee
authors.affiliation: BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, 48824, USA.|Department of Integrative Biology, Michigan State University, East Lansing, MI, 48824, USA.
authors.forename: William R
authors.initials: WR
authors.lastname: Pitchers
authors.affiliation: BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, 48824, USA.|Department of Integrative Biology, Michigan State University, East Lansing, MI, 48824, USA.
authors.forename: Sudarshan
authors.initials: S
authors.lastname: Chari
authors.affiliation: Genetics Graduate Program, Michigan State University, East Lansing, MI, 48824, USA. dworkin@mcmaster.ca.|BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI, 48824, USA. dworkin@mcmaster.ca.|Department of Integrative Biology, Michigan State University, East Lansing, MI, 48824, USA. dworkin@mcmaster.ca.|Department of Biology, McMaster University, Hamilton, Ontario, L8S 4K1, Canada. dworkin@mcmaster.ca.
authors.forename: Ian
authors.initials: I
authors.lastname: Dworkin
mesh_terms: D000465:Algorithms; D000818:Animals; D016208:Databases, Factual; D004331:Drosophila melanogaster; D005260:Female; D005838:Genotype; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D014921:Wings, Animal / Q000033:anatomy & histology*
keywords: Computer vision; Drosophila; Geometric morphometrics; Mutants; Phenomics; Wing shape