Fetal congenital heart disease echocardiogram screening based on DGACNN: adversarial oneclass classification combined with video transfer learning.

08:00 EDT 7th October 2019 | BioPortfolio

Summary of "Fetal congenital heart disease echocardiogram screening based on DGACNN: adversarial oneclass classification combined with video transfer learning."

Fetal congenital heart disease (FHD) is a common and serious congenital malformation in children. In Asia, FHD birth defect rates have reached as high as 9.3‰. For the early detection of birth defects and mortality, echocardiography remains the most effective method for screening fetal heart malformations. However, standard echocardiograms of the fetal heart, especially four-chamber view images, are difficult to obtain. In addition, the pathophysiological changes in fetal hearts during different pregnancy periods lead to ever-changing twodimensional fetal heart structures and hemodynamics, and it requires extensive professional knowledge to recognize and judge disease development. Thus, research on the automatic screening for FHD is necessary. In this paper, we proposed a new model named DGACNN that shows the best performance in recognizing FHD, achieving a rate of 85%. The motivation for this network is to deal with the problem that there are insufficient training datasets to train a robust model. There are many unlabeled video slices, but they are tough and time-consuming to annotate. Thus, how to use these unannotated video slices to improve the DGACNN capability for recognizing FHD, in terms of both recognition accuracy and robustness, is very meaningful for FHD screening. The architecture of DGACNN comprises two parts, that is, DANomaly and GACNN (Wgan-GP and CNN). DANomaly, similar to the ALOCC network, but incorporates cycle adversarial learning to train an end-to-end one-class classification (OCC) network that is more robust and has a higher accuracy than ALOCC in screening video slices. For the GACNN architecture, we use FCH(four chamber heart) video slices at around the endsystole, as screened by DANomaly, to train a WGAN-GP for the purpose of obtaining ideal low-level features that can robustly improve the FHD recognition accuracy. A few annotated video slices, as screened by DANomaly, can also be used for data augmentation so as to improve the FHD recognition further. The experiments show that the DGACNN outperforms other state-of-the-art networks by 1%-20% in recognizing FHD.A comparison experiment shows that the proposed network already outperforms the performance of expert cardiologists in recognizing FHD, reaching 84% in a test. Thus, the proposed architecture has high potential for helping cardiologists complete early FHD screenings.


Journal Details

This article was published in the following journal.

Name: IEEE transactions on medical imaging
ISSN: 1558-254X


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Medical and Biotech [MESH] Definitions

A nonreassuring fetal status (NRFS) indicating that the FETUS is compromised (American College of Obstetricians and Gynecologists 1988). It can be identified by sub-optimal values in FETAL HEART RATE; oxygenation of FETAL BLOOD; and other parameters.

The heart of the fetus of any viviparous animal. It refers to the heart in the postembryonic period and is differentiated from the embryonic heart (HEART/embryology) only on the basis of time.

A condition occurring in untreated or partially treated females with PHENYLKETONURIA when they become pregnant. This may result in damages to the FETUS, including MICROCEPHALY; MENTAL RETARDATION; congenital heart disease; FETAL GROWTH RETARDATION; and CRANIOFACIAL ABNORMALITIES. (From Am J Med Genet 1997 Mar 3;69(1):89-95)

Developmental abnormalities in any portion of the ATRIAL SEPTUM resulting in abnormal communications between the two upper chambers of the heart. Classification of atrial septal defects is based on location of the communication and types of incomplete fusion of atrial septa with the ENDOCARDIAL CUSHIONS in the fetal heart. They include ostium primum, ostium secundum, sinus venosus, and coronary sinus defects.

The identification of selected parameters in newborn infants by various tests, examinations, or other procedures. Screening may be performed by clinical or laboratory measures. A screening test is designed to sort out healthy neonates (INFANT, NEWBORN) from those not well, but the screening test is not intended as a diagnostic device, rather instead as epidemiologic.

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