title: Automatic mitral valve inflow measurements from Doppler echocardiography.
abstract: Doppler echocardiography is widely used for functional assessment of heart valves such as mitral valve. In current clinical work flow, to extract Doppler measurements, the envelopes of acquired Doppler spectra are manually traced. We propose a robust algorithm for automatically tracing the envelopes of mitral valve inflow Doppler spectra, which exhibit a large amount of variations in envelope shape and image appearance due to various disease conditions, patient/sonographer/instrument differences, etc. The algorithm is learning-based and capable of fully automatic detection and segmentation of the mitral inflow structures. Experiments show that the algorithm, running within one second, yields comparable performance to experts.
authors.affiliation: Integrated Data Systems, Siemens Corporate Research, Inc., Princeton, NJ, USA. jin-hyeong.park@siemens.com
authors.forename: JinHyeong
authors.initials: J
authors.lastname: Park
authors.forename: S Kevin
authors.initials: SK
authors.lastname: Zhou
authors.forename: John
authors.initials: J
authors.lastname: Jackson
authors.forename: Dorin
authors.initials: D
authors.lastname: Comaniciu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001783:Blood Flow Velocity / Q000502:physiology*; D015150:Echocardiography, Doppler / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008943:Mitral Valve / Q000000981:diagnostic imaging* / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012212:Rheology / Q000379:methods*; D012680:Sensitivity and Specificity