title: Towards automatic plan selection for radiotherapy of cervical cancer by fast automatic segmentation of cone beam CT scans.
abstract: We propose a method to automatically select a treatment plan for radiotherapy of cervical cancer using a Plan-of-the-Day procedure, in which multiple treatment plans are constructed prior to treatment. The method comprises a multi-atlas based segmentation algorithm that uses the selected treatment plan to choose between two atlas sets. This segmentation only requires two registration procedures and can therefore be used in clinical practice without using excessive computation time. Our method is validated on a dataset of 224 treatment fractions for 10 patients. In 37 cases (16%), no recommendation was made by the algorithm due to poor image quality or registration results. In 93% of the remaining cases a correct recommendation for a treatment plan was given.
authors.forename: Thomas
authors.initials: T
authors.lastname: Langerak
authors.forename: Sabrina
authors.initials: S
authors.lastname: Heijkoop
authors.forename: Sandra
authors.initials: S
authors.lastname: Quint
authors.forename: Jan-Willem
authors.initials: JW
authors.lastname: Mens
authors.forename: Ben
authors.initials: B
authors.lastname: Heijmen
authors.forename: Mischa
authors.initials: M
authors.lastname: Hoogeman
mesh_terms: D001185:Artificial Intelligence; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D005260:Female; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D061089:Radiotherapy, Image-Guided / Q000379:methods*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*