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All Journal Bulletin of Electrical Engineering and Informatics Majalah Obstetri dan Ginekologi Indonesian Journal of Obstetrics & Gynecology Science Indonesian Journal of Obstetrics and Gynecology (Majalah Obstetri dan Ginekologi Indonesia) SRIWIJAYA JOURNAL OF MEDICINE Indonesian Journal of Perinatology
Putri Mirani
Faculty of Medicine University of Indonesia Dr. Cipto Mangunkusumo Hospital Jakarta
Electrical & Electronics Engineering Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Nursing Public Health

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Residual pixel-wise semantic segmentation for assessing enlarged fetal heart: a preliminary study Roseno, Muhammad Taufik; Nurmaini, Siti; Rini, Dian Palupi; Saputra, Tommy; Mirani, Putri; Rachmatullah, Muhammad Naufal; Darmawahyuni, Annisa; Sapitri, Ade Iriani; Syaputra, Hadi
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.9244

Abstract

The four-chamber view is a crucial scan plane routinely employed in both second-trimester perinatal screening and fetal echocardiographic examinations. Sonographers typically measure biometrics in this plane, such as the cardiothoracic ratio (CTR) and heart axis, to diagnose fetal heart anomalies. However, due to the echocardiographic artifacts, the assessment not only suffers from low efficiency but also inconsistent results depending on the operators’ skills. This study proposes a residual pixel-wise semantic segmentation, which segmented the fetal heart and thoracic contours in a 4-chamber view for assessing an enlarged fetal heart condition. The accuracy of intersection-over-union (IoU) and dice coefficient similarity (DCS) is used for model validation to further regulate the evaluation procedure. We use 1174 US images, comprising about 560 enlarged heart images, and about 614 normal heart images. Out of these data, 248 images are used for unseen data, and the remaining for training/validation processes. The performance of the proposed model, when tested on unseen data, achieved satisfactory results with 97.71% accuracy, 90.36% IoU, and 94.93% DCS. These metrics collectively demonstrate the satisfactory performance of the proposed model compared to existing segmentation models. The outcomes underscore that the proposed model establishes a state-of-the-art standard for enlarged fetal heart detection.
Co-Authors Adnan Abadi, Adnan Agustria, Rizky Amir Fauzi Anang Ansyori Andrina, Hana Andriyani Liberty, Iche Ansyori, Muhammad Hatta Arjanggi, Kiagus Irawan Satria Awan Nurtjahyo Beumaputra, Adyatma Utama Darmawahyuni, Annisa Dian Palupi Rini HARTATI Iche Andriyani Liberty, Iche Andriyani Irfanuddin Jhonatan, Senna Moca Kesty, Cindy Krisna Murti Krisna, Ratih Legiran Legiran Mahadika, Febrinata Martadiansyah, Abarham Muhammad Naufal Rachmatullah Muhammad Taufik Roseno, Muhammad Taufik Nurwany, Raissa Nuswil Bernolian Pangemanan, Wim Theodorus PATIYUS AGUSTIANSYAH, PATIYUS Peby Maulina Lestari, Peby Maulina Prasetiyo, Muhammad Ath Thaariq Puspitasari, Dwi Cahya Putra, Hadrians Kesuma Ridwan, Metta Rania Rizani Amran Rizany, Selly Sapitri, Ade Iriani Saputra, Tommy Siti Nurmaini Stevanny, Bella Syamsuri, Ahmad Kurdi Syaputra, Hadi Theodorus Theodorus Usman, Fatimah Wim T. Pangemanan