title: Intensity-based image registration using scatter search.
abstract: OBJECTIVE
  We present a novel intensity-based algorithm for medical image registration (IR).
  
  
  METHODS
  The IR problem is formulated as a continuous optimization task, and our work focuses on the development of the optimization component. Our method is designed over an advanced scatter search template, and it uses a combination of restart and dynamic boundary mechanisms integrated within a multi-resolution strategy.
  
  
  RESULTS
  The experimental validation is performed over two datasets of human brain magnetic resonance imaging. The algorithm is evaluated in both a stand-alone registration application and an atlas-based segmentation process targeted to the deep brain structures, considering a total of 16 and 18 scenarios, respectively. Five established IR techniques, both feature- and intensity-based, are considered for comparison purposes, and ground-truth data is used to quantitatively assess the quality of the results. Our approach ranked first in both studies and it is able to outperform all competitors in 12 of 16 registration scenarios and in 14 of 18 registration-based segmentation tasks. A statistical analysis confirms with high confidence (p<0.014) the accuracy and applicability of our method.
  
  
  CONCLUSIONS
  With a proper, problem-specific design, scatter search is able to provide a robust, global optimization. The accuracy and reliability of the registration process are superior to those of classic gradient-based techniques.
authors.affiliation: Applications of Fuzzy Logic and Evolutionary Algorithms Research Unit, European Centre for Soft Computing, Calle Gonzalo Gutiérrez Quirós S/N, 33600 Mieres, Spain. Electronic address: andrea.valsecchi@softcomputing.es.
authors.forename: Andrea
authors.initials: A
authors.lastname: Valsecchi
authors.affiliation: Applications of Fuzzy Logic and Evolutionary Algorithms Research Unit, European Centre for Soft Computing, Calle Gonzalo Gutiérrez Quirós S/N, 33600 Mieres, Spain. Electronic address: sergio.damas@softcomputing.es.
authors.forename: Sergio
authors.initials: S
authors.lastname: Damas
authors.affiliation: Department of Computer Science, University of Jaén, Edificio Tecnológico y de Ingenierías A-3, Paraje Las Lagunillas S/N, 23071 Jaén, Spain. Electronic address: jslopez@ujaen.es.
authors.forename: José
authors.initials: J
authors.lastname: Santamaría
authors.affiliation: NeuroSpin, French Alternative Energies and Atomic Energy Commission, Bâtiment 145, Centre d'études de Saclay, 91191 Gif-sur-Yvette, France; Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière, Hôpital Pitié Salpêtrière, Boulevard de l'Hôpital 47, 75013 Paris, France. Electronic address: linda.marrakchi@gmail.com.
authors.forename: Linda
authors.initials: L
authors.lastname: Marrakchi-Kacem
mesh_terms: D000465:Algorithms; D001921:Brain; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods / Q000401:mortality*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results
keywords: Atlas-based segmentation; Global optimization; Heuristics; Image registration; Magnetic resonance imaging; Scatter search