title: Atlas-based automatic segmentation of MR images: validation study on the brainstem in radiotherapy context.
abstract: OBJECTIVE
  Brain tumor radiotherapy requires the volume measurements and the localization of several individual brain structures. Any tool that can assist the physician to perform the delineation would then be of great help. Among segmentation methods, those that are atlas-based are appealing because they are able to segment several structures simultaneously, while preserving the anatomy topology. This study aims to evaluate such a method in a clinical context.
  
  
  METHODS
  The brain atlas is made of two three-dimensional (3D) volumes: the first is an artificial 3D magnetic resonance imaging (MRI); the second consists of the segmented structures in this artificial MRI. The elastic registration of the artificial 3D MRI against a patient 3D MRI dataset yields an elastic transformation that can be applied to the labeled image. The elastic transformation is obtained by minimizing the sum of the square differences of the image intensities and derived from the optical flow principle. This automatic delineation (AD) enables the mapping of the segmented structures onto the patient MRI. Parameters of the AD have been optimized on a set of 20 patients. Results are obtained on a series of 6 patients' MRI. A comprehensive validation of the AD has been conducted on performance of atlas-based segmentation in a clinical context with volume, position, sensitivity, and specificity that are compared by a panel of seven experimented physicians for the brain tumor treatments.
  
  
  RESULTS
  Expert interobserver volume variability ranged from 16.70 cm(3) to 41.26 cm(3). For patients, the ratio of minimal to maximal volume ranged from 48% to 70%. Median volume varied from 19.47 cm(3) to 27.66 cm(3) and volume of the brainstem calculated by AD varied from 17.75 cm(3) to 24.54 cm(3). Medians of experts ranged, respectively, for sensitivity and specificity, from 0.75 to 0.98 and from 0.85 to 0.99. Median of AD were, respectively, 0.77 and 0.97. Mean of experts ranged, respectively, from 0.78 to 0.97 and from 0.86 to 0.99. Mean of AD were, respectively, 0.76 and 0.97.
  
  
  CONCLUSIONS
  Results demonstrate that the method is repeatable, provides a good trade-off between accuracy and robustness, and leads to reproducible segmentation and labeling. These results can be improved by enriching the atlas with the rough information of tumor or by using different laws of deformation for the different structures. Qualitative results also suggest that this method can be used for automatic segmentation of other organs such as neck, thorax, abdomen, pelvis, and limbs.
authors.affiliation: Projet Epidaure, Institut National de Recherche en Informatique et Automatique, Sophia Antipolis, France. pierre-yves.bondiau@cal.nice.fnclcc.fr
authors.forename: Pierre-Yves
authors.initials: PY
authors.lastname: Bondiau
authors.forename: Grégoire
authors.initials: G
authors.lastname: Malandain
authors.forename: Stéphane
authors.initials: S
authors.lastname: Chanalet
authors.forename: Pierre-Yves
authors.initials: PY
authors.lastname: Marcy
authors.forename: Jean-Louis
authors.initials: JL
authors.lastname: Habrand
authors.forename: François
authors.initials: F
authors.lastname: Fauchon
authors.forename: Philippe
authors.initials: P
authors.lastname: Paquis
authors.forename: Adel
authors.initials: A
authors.lastname: Courdi
authors.forename: Olivier
authors.initials: O
authors.lastname: Commowick
authors.forename: Isabelle
authors.initials: I
authors.lastname: Rutten
authors.forename: Nicholas
authors.initials: N
authors.lastname: Ayache
mesh_terms: D000465:Algorithms; D000716:Anatomy, Artistic / Q000379:methods; D001932:Brain Neoplasms / Q000473:pathology* / Q000532:radiotherapy; D001933:Brain Stem / Q000033:anatomy & histology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008488:Medical Illustration; D015588:Observer Variation; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity