title: Automatic segmentation of pelvic structures from magnetic resonance images for prostate cancer radiotherapy.
abstract: OBJECTIVE
  Target-volume and organ-at-risk delineation is a time-consuming task in radiotherapy planning. The development of automated segmentation tools remains problematic, because of pelvic organ shape variability. We evaluate a three-dimensional (3D), deformable-model approach and a seeded region-growing algorithm for automatic delineation of the prostate and organs-at-risk on magnetic resonance images.
  
  
  METHODS
  Manual and automatic delineation were compared in 24 patients using a sagittal T2-weighted (T2-w) turbo spin echo (TSE) sequence and an axial T1-weighted (T1-w) 3D fast-field echo (FFE) or TSE sequence. For automatic prostate delineation, an organ model-based method was used. Prostates without seminal vesicles were delineated as the clinical target volume (CTV). For automatic bladder and rectum delineation, a seeded region-growing method was used. Manual contouring was considered the reference method. The following parameters were measured: volume ratio (Vr) (automatic/manual), volume overlap (Vo) (ratio of the volume of intersection to the volume of union; optimal value = 1), and correctly delineated volume (Vc) (percent ratio of the volume of intersection to the manually defined volume; optimal value = 100).
  
  
  RESULTS
  For the CTV, the Vr, Vo, and Vc were 1.13 (+/-0.1 SD), 0.78 (+/-0.05 SD), and 94.75 (+/-3.3 SD), respectively. For the rectum, the Vr, Vo, and Vc were 0.97 (+/-0.1 SD), 0.78 (+/-0.06 SD), and 86.52 (+/-5 SD), respectively. For the bladder, the Vr, Vo, and Vc were 0.95 (+/-0.03 SD), 0.88 (+/-0.03 SD), and 91.29 (+/-3.1 SD), respectively.
  
  
  CONCLUSIONS
  Our results show that the organ-model method is robust, and results in reproducible prostate segmentation with minor interactive corrections. For automatic bladder and rectum delineation, magnetic resonance imaging soft-tissue contrast enables the use of region-growing methods.
authors.affiliation: Département Universitaire de Radiothérapie, Centre Oscar Lambret, Université Lille II, Lille, France. d-pasquier@o-lambret.fr
authors.forename: David
authors.initials: D
authors.lastname: Pasquier
authors.forename: Thomas
authors.initials: T
authors.lastname: Lacornerie
authors.forename: Maximilien
authors.initials: M
authors.lastname: Vermandel
authors.forename: Jean
authors.initials: J
authors.lastname: Rousseau
authors.forename: Eric
authors.initials: E
authors.lastname: Lartigau
authors.forename: Nacim
authors.initials: N
authors.lastname: Betrouni
mesh_terms: D000465:Algorithms; D005240:Feasibility Studies; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D010388:Pelvis / Q000033:anatomy & histology; D011467:Prostate / Q000033:anatomy & histology; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000532:radiotherapy; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012007:Rectum / Q000033:anatomy & histology; D018709:Statistics, Nonparametric; D013679:Technology, Radiologic / Q000379:methods; D047368:Tumor Burden; D001743:Urinary Bladder / Q000033:anatomy & histology