Automated Analysis of Mitral Inflow Doppler using Convolutional Neural Networks

Jevgeni Jevsikov, Elisabeth Sarah Lane, Catherine C Stowell, Matthew J Shun-shin, Darrel P Francis, Massoud Zolgharni

Keywords: Cardiac imaging, Echocardiography, Deep learning

TL;DR: The feasibility of using neural networks to fully automate the process of mitral valve inflow measurements.

Abstract: Doppler echocardiography is commonly used for functional assessment of heart valves such as mitral valve. Currently, the measurements are made manually which is a laborious and subjective process. We have demonstrated the feasibility of using neural networks to fully automate the process of mitral valve inflow measurements. Experiments show that the automated system yields comparable performance to the experts.

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Paper Type: novel methodological ideas without extensive validation

Primary Subject Area: Transfer Learning and Domain Adaptation

Secondary Subject Area: Detection and Diagnosis

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