Deep learning has become a recent explosion in our everyday lives. Being one of the leading machine learning tools among various tools, deep learning contributes a lot to image analysis and the vision of the computer. This tool is considered enormous for image analysis, especially in detecting fetal cardiac abnormalities in a parallel computing environment. Screening congenital cardiac disease (CCD) is challenging in achieving accuracy in terms of diagnoses concerning the manual process. Hence in this proposed work, optimized ultrasound image (USI) based Artificial Neural Network (ANN), a deep learning tool, has proven in exploiting the dissimilitude prognoses of cardiomyopathies and in predicting perinatal mortality of congenital cardiac disease (CCD). Fetal Cardiac parameters are evaluated using the myocardial performance index (MPI), a biomarker of global cardiac function providing statistics on various periods during diastolic and systolic phases. This paper also discusses some potential trends of deep learning application in ultrasound image analysis in detecting and predicting the abnormalities in fetal cardiac function.
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