title: Optimal number of atlases and label fusion for automatic multi-atlas-based brachial plexus contouring in radiotherapy treatment planning.
abstract: BACKGROUND
  The present study aimed to define the optimal number of atlases for automatic multi-atlas-based brachial plexus (BP) segmentation and to compare Simultaneous Truth and Performance Level Estimation (STAPLE) label fusion with Patch label fusion using the ADMIRE® software. The accuracy of the autosegmentations was measured by comparing all of the generated autosegmentations with the anatomically validated gold standard segmentations that were developed using cadavers.
  
  
  METHODS
  Twelve cadaver computed tomography (CT) atlases were used for automatic multi-atlas-based segmentation. To determine the optimal number of atlases, one atlas was selected as a patient and the 11 remaining atlases were registered onto this patient using a deformable image registration algorithm. Next, label fusion was performed by using every possible combination of 2 to 11 atlases, once using STAPLE and once using Patch. This procedure was repeated for every atlas as a patient. The similarity of the generated automatic BP segmentations and the gold standard segmentation was measured by calculating the average Dice similarity (DSC), Jaccard (JI) and True positive rate (TPR) for each number of atlases. These similarity indices were compared for the different number of atlases using an equivalence trial and for the two label fusion groups using an independent sample-t test.
  
  
  RESULTS
  DSC's and JI's were highest when using nine atlases with both STAPLE (average DSC = 0,532; JI = 0,369) and Patch (average DSC = 0,530; JI = 0,370). When comparing both label fusion algorithms using 9 atlases for both, DSC and JI values were not significantly different. However, significantly higher TPR values were achieved in favour of STAPLE (p < 0,001). When fewer than four atlases were used, STAPLE produced significantly lower DSC, JI and TPR values than did Patch (p = 0,0048).
  
  
  CONCLUSIONS
  Using 9 atlases with STAPLE label fusion resulted in the most accurate BP autosegmentations (average DSC = 0,532; JI = 0,369 and TPR = 0,760). Only when using fewer than four atlases did the Patch label fusion results in a significantly more accurate autosegmentation than STAPLE.
authors.affiliation: Department of Anatomy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. joris.vandevelde@ugent.be.|Department of Radiotherapy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. joris.vandevelde@ugent.be.
authors.forename: Joris
authors.initials: J
authors.lastname: Van de Velde
authors.affiliation: Department of Anatomy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. Johan.Wouters@ugent.be.
authors.forename: Johan
authors.initials: J
authors.lastname: Wouters
authors.affiliation: Department of Radiotherapy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. Tom.Vercauteren@uzgent.be.
authors.forename: Tom
authors.initials: T
authors.lastname: Vercauteren
authors.affiliation: Department of Radiotherapy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. Werner.Degersem@uzgent.be.
authors.forename: Werner
authors.initials: W
authors.lastname: De Gersem
authors.affiliation: Department of Radiology, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. Eric.achten@ugent.be.
authors.forename: Eric
authors.initials: E
authors.lastname: Achten
authors.affiliation: Department of Radiotherapy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. Wilfried.Deneve@uzgent.be.
authors.forename: Wilfried
authors.initials: W
authors.lastname: De Neve
authors.affiliation: Department of Anatomy, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium. Tom.Vanhoof@ugent.be.
authors.forename: Tom
authors.initials: T
authors.lastname: Van Hoof
mesh_terms: D000465:Algorithms; D001917:Brachial Plexus / Q000528:radiation effects*; D002102:Cadaver; D005189:False Positive Reactions; D006801:Humans; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011874:Radiometry; D011878:Radiotherapy / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D014057:Tomography, X-Ray Computed