Automatic localized analysis of longitudinal cartilage changes

TitleAutomatic localized analysis of longitudinal cartilage changes
Publication TypeThesis
Year of Publication2014
AuthorsShan L
UniversityThe university of North Carolina at Chapel Hill
Thesis Typephd

Osteoarthritis (OA) is the most common form of arthritis; it is characterized by the loss of cartilage. Automatic quantitative methods are needed to screen large image databases to assess changes in cartilage morphology. This dissertation presents an automatic analysis method to quantitatively analyze longitudinal cartilage changes from knee magnetic resonance (MR) images. A novel robust automatic cartilage segmentation method is proposed to overcome the limitations of existing cartilage segmentation methods. The dissertation presents a new and general convex three-label segmentation approach to ensure the separation of touching objects, i.e., femoral and tibial cartilage. Anisotropic spatial regularization is introduced to avoid over-regularization by isotropic regularization on thin objects. Temporal regularization is further incorporated to encourage temporally-consistent segmentations across time points for longitudinal data. The state-of-the-art analysis of cartilage changes relies on the subdivision of cartilage, which is coarse and purely geometric whereas cartilage loss is a local thinning process and exhibits spatial nonuniformity. A statistical analysis method is proposed to study localized longitudinal cartilage thickness changes by establishing spatial correspondences across time and between subjects. The method is general and can be applied to nonuniform morphological changes in other diseases.

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