Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model

Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model

Abstract Echocardiographic interpretation during the prenatal or postnatal period is important for diagnosing cardiac septal abnormalities. However, manual interpretation can be time consuming and subject to human error. Automatic segmentation of echocardiogram can support cardiologists in making an...

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Bibliographic Details
Main Authors: Siti Nurmaini, Ade Iriani Sapitri, Bambang Tutuko, Muhammad Naufal Rachmatullah, Dian Palupi Rini, Annisa Darmawahyuni, Firdaus Firdaus, Satria Mandala, Ria Nova, Nuswil Bernolian
Format: Article
Language:English
Published: BMC 2023-09-01
Series:BMC Bioinformatics
Subjects:
Cardiac septal defect
Classification
Deep learning
Echocardiography
Segmentation
Online Access:https://doi.org/10.1186/s12859-023-05493-9

Internet

https://doi.org/10.1186/s12859-023-05493-9

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