title: The use of atlas registration and graph cuts for prostate segmentation in magnetic resonance images.
abstract: OBJECTIVE
  An automatic method for 3D prostate segmentation in magnetic resonance (MR) images is presented for planning image-guided radiotherapy treatment of prostate cancer.
  
  
  METHODS
  A spatial prior based on intersubject atlas registration is combined with organ-specific intensity information in a graph cut segmentation framework. The segmentation is tested on 67 axial T2-weighted MR images in a leave-one-out cross validation experiment and compared with both manual reference segmentations and with multiatlas-based segmentations using majority voting atlas fusion. The impact of atlas selection is investigated in both the traditional atlas-based segmentation and the new graph cut method that combines atlas and intensity information in order to improve the segmentation accuracy. Best results were achieved using the method that combines intensity information, shape information, and atlas selection in the graph cut framework.
  
  
  RESULTS
  A mean Dice similarity coefficient (DSC) of 0.88 and a mean surface distance (MSD) of 1.45 mm with respect to the manual delineation were achieved.
  
  
  CONCLUSIONS
  This approaches the interobserver DSC of 0.90 and interobserver MSD 0f 1.15 mm and is comparable to other studies performing prostate segmentation in MR.
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg 9220, Denmark.
authors.forename: Anne Sofie
authors.initials: AS
authors.lastname: Korsager
authors.affiliation: Biomedical Imaging Group of Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam 3015 GE Rotterdam, The Netherlands.
authors.forename: Valerio
authors.initials: V
authors.lastname: Fortunati
authors.affiliation: Biomedical Imaging Group of Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam 3015 GE Rotterdam, The Netherlands.
authors.forename: Fedde
authors.initials: F
authors.lastname: van der Lijn
authors.affiliation: Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg 9220, Denmark.
authors.forename: Jesper
authors.initials: J
authors.lastname: Carl
authors.affiliation: Biomedical Imaging Group of Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam 3015 GE Rotterdam, The Netherlands.
authors.forename: Wiro
authors.initials: W
authors.lastname: Niessen
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg 9220, Denmark.
authors.forename: Lasse Riis
authors.initials: LR
authors.lastname: Østergaard
authors.affiliation: Biomedical Imaging Group of Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam 3015 GE Rotterdam, The Netherlands.
authors.forename: Theo
authors.initials: T
authors.lastname: van Walsum
mesh_terms: D001271:Atlases as Topic; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011467:Prostate / Q000033:anatomy & histology* / Q000473:pathology; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D011859:Radiography; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods