TY - JOUR
T1 - Doppler echocardiography flow-velocity image analysis for patients with atrial fibrillation
AU - Greenspan, Hayit
AU - Shechner, Oron
AU - Scheinowitz, Mickey
AU - Feinberg, Micha S.
PY - 2005/8
Y1 - 2005/8
N2 - Currently, Doppler echocardiography analysis is performed manually. An automated method that analyzes the Doppler signal can potentially improve accuracy and result in a powerful tool for noninvasive evaluation of cardiac hemodynamics, especially for patients with atrial fibrillation, where multiple samples are needed to obtain an accurate averaged measurement. The aim of this study was to develop an automated method for Doppler analysis based on image processing and computer vision algorithms. Images were obtained from the mitral valve and the tricuspid valve Doppler tracings from 45 patients, 20 with normal sinus rhythm and 25 with atrial fibrillation. The proposed algorithm automatically detects the maximal velocity envelope of the spectral Doppler ultrasound tracings. Averaged values for the time velocity integral, peak mitral inflow velocity and peak tricuspid regurgitation velocity were calculated for multiple beats available in a single screen frame. Measurements extracted automatically from the maximal velocity envelope were compared to measurements obtained manually by two expert technicians. High linear correlation (r) was found between the automatically- and the manually-extracted parameters (0.95 < r < 0.99). A smaller variation was found in most cases between the manually-calculated average beat and the automated average beat (bias value between 3.8% and 5.2%) than between the manually-calculated average beat and the selection of a representative beat (bias value between 6.2% and -2.6%). The newly-developed automated method offers a new, accurate and reliable clinical tool, particularly for the assessment of patients with irregular heart rate.
AB - Currently, Doppler echocardiography analysis is performed manually. An automated method that analyzes the Doppler signal can potentially improve accuracy and result in a powerful tool for noninvasive evaluation of cardiac hemodynamics, especially for patients with atrial fibrillation, where multiple samples are needed to obtain an accurate averaged measurement. The aim of this study was to develop an automated method for Doppler analysis based on image processing and computer vision algorithms. Images were obtained from the mitral valve and the tricuspid valve Doppler tracings from 45 patients, 20 with normal sinus rhythm and 25 with atrial fibrillation. The proposed algorithm automatically detects the maximal velocity envelope of the spectral Doppler ultrasound tracings. Averaged values for the time velocity integral, peak mitral inflow velocity and peak tricuspid regurgitation velocity were calculated for multiple beats available in a single screen frame. Measurements extracted automatically from the maximal velocity envelope were compared to measurements obtained manually by two expert technicians. High linear correlation (r) was found between the automatically- and the manually-extracted parameters (0.95 < r < 0.99). A smaller variation was found in most cases between the manually-calculated average beat and the automated average beat (bias value between 3.8% and 5.2%) than between the manually-calculated average beat and the selection of a representative beat (bias value between 6.2% and -2.6%). The newly-developed automated method offers a new, accurate and reliable clinical tool, particularly for the assessment of patients with irregular heart rate.
KW - Atrial fibrillation
KW - Automated system
KW - Blood flow velocity
KW - Doppler echocardiography
KW - Edge detection
KW - Image processing
KW - Maximal velocity envelope
UR - http://www.scopus.com/inward/record.url?scp=23644447583&partnerID=8YFLogxK
U2 - 10.1016/j.ultrasmedbio.2005.04.016
DO - 10.1016/j.ultrasmedbio.2005.04.016
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AN - SCOPUS:23644447583
SN - 0301-5629
VL - 31
SP - 1031
EP - 1040
JO - Ultrasound in Medicine and Biology
JF - Ultrasound in Medicine and Biology
IS - 8
ER -