Automatic extraction of disease-specific features from Doppler images

Mohammadreza Negahdar; Mehdi Moradi; Nripesh Parajuli; Tanveer Syeda-Mahmood

doi:10.1117/12.2253956

3 March 2017 Automatic extraction of disease-specific features from Doppler images

Mohammadreza Negahdar, Mehdi Moradi, Nripesh Parajuli, Tanveer Syeda-Mahmood

Proceedings Volume 10134, Medical Imaging 2017: Computer-Aided Diagnosis; 101340N (2017) https://doi.org/10.1117/12.2253956
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Flow Doppler imaging is widely used by clinicians to detect diseases of the valves. In particular, continuous wave (CW) Doppler mode scan is routinely done during echocardiography and shows Doppler signal traces over multiple heart cycles. Traditionally, echocardiographers have manually traced such velocity envelopes to extract measurements such as decay time and pressure gradient which are then matched to normal and abnormal values based on clinical guidelines. In this paper, we present a fully automatic approach to deriving these measurements for aortic stenosis retrospectively from echocardiography videos. Comparison of our method with measurements made by echocardiographers shows large agreement as well as identification of new cases missed by echocardiographers.

Conference Presentation

Citation Download Citation

Mohammadreza Negahdar, Mehdi Moradi, Nripesh Parajuli, and Tanveer Syeda-Mahmood "Automatic extraction of disease-specific features from Doppler images", Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101340N (3 March 2017); https://doi.org/10.1117/12.2253956

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