title: A multi-time-point modality-agnostic patch-based method for lesion filling in multiple sclerosis.
abstract: Multiple sclerosis lesions influence the process of image analysis, leading to tissue segmentation problems and biased morphometric estimates. Existing techniques try to reduce this bias by filling all lesions as normal-appearing white matter on T1-weighted images, considering each time-point separately. However, due to lesion segmentation errors and the presence of structures adjacent to the lesions, such as the ventricles and deep grey matter nuclei, filling all lesions with white matter-like intensities introduces errors and artefacts. In this paper, we present a novel lesion filling strategy inspired by in-painting techniques used in computer graphics applications for image completion. The proposed technique uses a five-dimensional (5D), patch-based (multi-modality and multi-time-point), Non-Local Means algorithm that fills lesions with the most plausible texture. We demonstrate that this strategy introduces less bias, fewer artefacts and spurious edges than the current, publicly available techniques. The proposed method is modality-agnostic and can be applied to multiple time-points simultaneously. In addition, it preserves anatomical structures and signal-to-noise characteristics even when the lesions are neighbouring grey matter or cerebrospinal fluid, and avoids excess of blurring or rasterisation due to the choice of the segmentation plane, shape of the lesions, and their size and/or location.
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, Gower Street, London, WC1E 6BT, UK; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, 1st Floor, Russell Square House, 10-12 Russell Square, London WC1B 5EH, UK. Electronic address: f.carrasco@ucl.ac.uk.
authors.forename: Ferran
authors.initials: F
authors.lastname: Prados
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, Gower Street, London, WC1E 6BT, UK.
authors.forename: Manuel Jorge
authors.initials: MJ
authors.lastname: Cardoso
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, Gower Street, London, WC1E 6BT, UK.
authors.forename: Baris
authors.initials: B
authors.lastname: Kanber
authors.affiliation: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, 1st Floor, Russell Square House, 10-12 Russell Square, London WC1B 5EH, UK.
authors.forename: Olga
authors.initials: O
authors.lastname: Ciccarelli
authors.affiliation: Department of Neuroinflammation, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK.
authors.forename: Raju
authors.initials: R
authors.lastname: Kapoor
authors.affiliation: NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, 1st Floor, Russell Square House, 10-12 Russell Square, London WC1B 5EH, UK; Brain MRI 3T Center, C. Mondino National Neurological Institute, Pavia, Italy.
authors.forename: Claudia A M
authors.initials: CAM
authors.lastname: Gandini Wheeler-Kingshott
authors.affiliation: Translational Imaging Group, Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, Gower Street, London, WC1E 6BT, UK; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
mesh_terms: D000328:Adult; D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging* / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging* / Q000473:pathology*; D012815:Signal Processing, Computer-Assisted; D066127:White Matter / Q000000981:diagnostic imaging / Q000473:pathology
keywords: Artefacts; Error correction; Lesions; MRI; Multiple sclerosis; Segmentation errors