title: Coupled registration-segmentation: application to femur analysis with intra-subject multiple levels of detail MRI data.
abstract: The acquisition of intra-subject data from multiple images is routinely performed to provide complementary information where a single image is not sufficient. However, these images are not always co-registered since they are acquired with different scanners, affected by subject's movements during scans, and consist of different image attributes, e.g. image resolution, field of view (FOV) and intensity distributions. In this study, we propose a coupled registration-segmentation framework that simultaneously registers and segments intra-subject images with different image attributes. The proposed coupled framework is demonstrated with the processing of multiple level of detail (LOD) MRI acquisitions of the hip joint structures, which yield efficient and automated approaches to analyze soft tissues (from high-resolution MRI) in conjunction with the entire hip joint structures (from low resolution MRI).
authors.affiliation: MIRALab, University of Geneva, Switzerland. schmid@miralab.ch
authors.forename: Jérôme
authors.initials: J
authors.lastname: Schmid
authors.forename: Jinman
authors.initials: J
authors.lastname: Kim
authors.forename: Nadia
authors.initials: N
authors.lastname: Magnenat-Thalmann
mesh_terms: D000465:Algorithms; D005269:Femur / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique