FetalNet: Low-light fetal echocardiography enhancement and dense convolutional network classifier for improving heart defect prediction

FetalNet: Low-light fetal echocardiography enhancement and dense convolutional network classifier for improving heart defect prediction

Background: Fetal heart defect (FHD) examination by ultrasound (US) is challenging because it involves low light, contrast, and brightness. Inadequate US images of fetal echocardiography play an important role in the failure to detect FHDs manually. The automatic interpretation of fetal echocardiogr...

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Bibliographic Details
Main Authors: Sutarno Sutarno, Siti Nurmaini, Radiyati Umi Partan, Ade Iriani Sapitri, Bambang Tutuko, Muhammad Naufal Rachmatullah, Annisa Darmawahyuni, Firdaus Firdaus, Nuswil Bernolian, Deny Sulistiyo
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Deep learning
Ultrasound
Congenital heart disease
Low light image enhancement
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914822002738

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http://www.sciencedirect.com/science/article/pii/S2352914822002738

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