title: Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation.
abstract: Rectal tumour segmentation in dynamic contrast-enhanced MRI (DCE-MRI) is a challenging task, and an automated and consistent method would be highly desirable to improve the modelling and prediction of patient outcomes from tissue contrast enhancement characteristics - particularly in routine clinical practice. A framework is developed to automate DCE-MRI tumour segmentation, by introducing: perfusion-supervoxels to over-segment and classify DCE-MRI volumes using the dynamic contrast enhancement characteristics; and the pieces-of-parts graphical model, which adds global (anatomic) constraints that further refine the supervoxel components that comprise the tumour. The framework was evaluated on 23 DCE-MRI scans of patients with rectal adenocarcinomas, and achieved a voxelwise area-under the receiver operating characteristic curve (AUC) of 0.97 compared to expert delineations. Creating a binary tumour segmentation, 21 of the 23 cases were segmented correctly with a median Dice similarity coefficient (DSC) of 0.63, which is close to the inter-rater variability of this challenging task. A second study is also included to demonstrate the method's generalisability and achieved a DSC of 0.71. The framework achieves promising results for the underexplored area of rectal tumour segmentation in DCE-MRI, and the methods have potential to be applied to other DCE-MRI and supervoxel segmentation problems.
authors.affiliation: Institute of Biomedical Engineering, Department of Engineering Science, Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, UK. Electronic address: benjamin.irving@eng.ox.ac.uk.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Irving
authors.affiliation: Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford OX3 7LE, UK.
authors.forename: James M
authors.initials: JM
authors.lastname: Franklin
authors.affiliation: Institute of Biomedical Engineering, Department of Engineering Science, Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, UK.
authors.forename: Bartłomiej W
authors.initials: BW
authors.lastname: Papież
authors.affiliation: Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford OX3 7LE, UK.
authors.forename: Ewan M
authors.initials: EM
authors.lastname: Anderson
authors.affiliation: Department of Oncology, Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, UK.
authors.forename: Ricky A
authors.initials: RA
authors.lastname: Sharma
authors.affiliation: Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford OX3 7LE, UK.
authors.forename: Fergus V
authors.initials: FV
authors.lastname: Gleeson
authors.affiliation: Department of Oncology, Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, UK.
authors.forename: Sir Michael
authors.initials: SM
authors.lastname: Brady
authors.affiliation: Institute of Biomedical Engineering, Department of Engineering Science, Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, UK; Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas' Hospital, London SE1 7EH, UK.
authors.forename: Julia A
authors.initials: JA
authors.lastname: Schnabel
mesh_terms: D000465:Algorithms; D003287:Contrast Media; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D012004:Rectal Neoplasms / Q000000981:diagnostic imaging*
chemical_list: D003287:Contrast Media
keywords: Classification; DCE-MRI; Parts-based graphical models; Rectal tumour; Segmentation; Supervoxel