Pelvic floor disorders such as Pelvic Organ Prolapse (POP) negatively impact the health and quality of life of millions of women worldwide. POP is characterized by the descent of the pelvic organs into the vagina due to compromised connective tissue support, resulting in discomfort and urinary/fecal incontinence. Magnetic Resonance Imaging (MRI) has been used to aid in the quantification of these anatomical changes, however the inter- and intra-observer repeatability necessary to make reliable conclusions about changes in anatomical positioning is questioned using current methods. The aim of this study was to quantify the degree of variability produced from inter-observer manual tracings of the vagina from MRI scans using a statistical shape matching approach.

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