Automatic Mitral Valve Inflow Measurements from Doppler Echocardiography

Authors:
Jinhyeong Park;S. Kevin Zhou;John Jackson;Dorin Comaniciu
Affiliations:
Integrated Data Systems,Siemens Corporate Research, Inc., , Princeton, USA;Integrated Data Systems,Siemens Corporate Research, Inc., , Princeton, USA;Ultrasound Division, Siemens Medical Solution, , USA;Integrated Data Systems,Siemens Corporate Research, Inc., , Princeton, USA
Venue:
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Year:
2008

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Database-Guided Segmentation of Anatomical Structures with Complex Appearance

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02

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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.