Semi-Automatic Delineation of the Mitral Valve from Clinical Four-Dimensional Ultrasound Imaging

Successful clinical treatment of mitral valve disease is dependent on understanding the complexities of patient-specific valve behavior. Mechanical models of the mitral valve, designed to predict valve closure and generated using patient-specific measurements, have proven to be effective tools for studying valve behavior. To be clinically feasible, these models need to be generated from ultrasound images, which are commonly acquired during the diagnosis and treatment of patients. However, methods of generating accurate models from ultrasound data using minimal user-input and interaction are not available. This work presents methods by which a patient-specific mitral valve model (annulus and leaflets) can be generated from three-dimensional ultrasound. The method first identifies the mitral annulus in a user-specified frame just after valve closure using only a roughly placed valve center point. We find the annulus as the location where the thin leaflet tissue intersects the thicker surrounding tissue. Comparing the results to manual delineations made by experts, we found an average RMS error of 1.81±0.78mm. A valve state (open versus closed) predictor and a constrained optical flow algorithm are then used to segment the annulus in the remaining frames in the ultrasound sequence. We compared the automated tracking results to manual delineations made by experts and found an average RMS difference of 1.67±0.63mm. The location of the leaflets in a user-specified frame just before valve closure is then automatically found by using the annulus as a means of limiting