Analysis of cardiac hemodynamics from Doppler echocardiography videos allows (i) precise diagnosis of circulatory disorders, (ii) assessment of cardiovascular function and (iii) orientation of medical intervention. Th...
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ISBN:
(纸本)9783031602146;9783031602153
Analysis of cardiac hemodynamics from Doppler echocardiography videos allows (i) precise diagnosis of circulatory disorders, (ii) assessment of cardiovascular function and (iii) orientation of medical intervention. The analysis of cardiac hemodynamics is based on determining the movement of blood between successive images. The used techniques fall into two categories: those estimating displacement vectors for each region of interest and those that operate at pixel level. The two main difficulties lie, on the one hand, in the limited availability of cardiac ultrasound data due to confidentiality restrictions and, on the other, in the complexity of the data annotation task, which requires specialist expertise and is time-consuming. Our proposed approach addresses this limitation by proposing a new algorithm for estimating blood displacement vectors based on supervised deep learning. Our contribution consists in including an automatic annotation step for the video database in order to use the labelled images as ground truth. This approach includes three main stages: (1) data preparation and selection of regions of interest (ROIs), (2) automatic annotation using the optical flow method and (3) motion estimation using deep learning (DL) models. This new algorithm has been validated on a Doppler echocardiography video base. The performance of the automatic annotation achieves AEE = 1.36 and the DL-based displacement estimation optimize the AEE value up to 0.013. Our novel approach holds considerable potential for accurately estimating and visualizing flow fields in clinical context. With an encouraging and a promising outcome, providing a constructive foundation for further investigation and inspiring the exploration of new perspectives for the diagnosis and treatment of cardiovascular diseases.
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