Mitral Valve Segmentation and Tracking from Transthoracic Echocardiography Using Deep Learning

Valvular heart diseases (VHDs) pose a significant public health burden, and deciding the best treatment strategy necessitates accurate assessment of heart valve function. Transthoracic echocardiography (TTE) is the key modality to evaluate VHDs, but the lack of standardized quantitative measurements leads to subjective and time-consuming assessments. We aimed to use deep learning to automate the extraction of mitral valve (MV) leaflets and annular hinge points from echocardiograms of the MV, improving standardization and reducing workload in quantitative assessment of MV disease.

Source: Ultrasound in Medicine and Biology - February 9, 2024 Category: Radiology Authors: Sigurd Vangen Wifstad, Henrik Agerup Kildahl, Bj ørnar Grenne, Espen Holte, Ståle Wågen Hauge, Sigbjørn Sæbø, Desalew Mekonnen, Berhanu Nega, Rune Haaverstad, Mette-Elise Estensen, Håvard Dalen, Lasse Lovstakken Tags: Original Contribution Source Type: research