Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images
Summary: Several reviews have been conducted regarding artificial intelligence (AI) techniques to improve pregnancy outcomes. But they are not focusing on ultrasound images. This survey aims to explore how AI can assist with fetal growth monitoring via ultrasound image. We reported our findings usin...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-08-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004222009853 |
| _version_ | 1818474810428096512 |
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| author | Mahmood Alzubaidi Marco Agus Khalid Alyafei Khaled A. Althelaya Uzair Shah Alaa Abd-Alrazaq Mohammed Anbar Michel Makhlouf Mowafa Househ |
| author_facet | Mahmood Alzubaidi Marco Agus Khalid Alyafei Khaled A. Althelaya Uzair Shah Alaa Abd-Alrazaq Mohammed Anbar Michel Makhlouf Mowafa Househ |
| author_sort | Mahmood Alzubaidi |
| collection | DOAJ |
| description | Summary: Several reviews have been conducted regarding artificial intelligence (AI) techniques to improve pregnancy outcomes. But they are not focusing on ultrasound images. This survey aims to explore how AI can assist with fetal growth monitoring via ultrasound image. We reported our findings using the guidelines for PRISMA. We conducted a comprehensive search of eight bibliographic databases. Out of 1269 studies 107 are included. We found that 2D ultrasound images were more popular (88) than 3D and 4D ultrasound images (19). Classification is the most used method (42), followed by segmentation (31), classification integrated with segmentation (16) and other miscellaneous methods such as object-detection, regression, and reinforcement learning (18). The most common areas that gained traction within the pregnancy domain were the fetus head (43), fetus body (31), fetus heart (13), fetus abdomen (10), and the fetus face (10). This survey will promote the development of improved AI models for fetal clinical applications. |
| first_indexed | 2024-04-14T04:42:16Z |
| format | Article |
| id | doaj.art-d42cc4e2e26349e3b01680f5856008bf |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-04-14T04:42:16Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-d42cc4e2e26349e3b01680f5856008bf2022-12-22T02:11:38ZengElsevieriScience2589-00422022-08-01258104713Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound imagesMahmood Alzubaidi0Marco Agus1Khalid Alyafei2Khaled A. Althelaya3Uzair Shah4Alaa Abd-Alrazaq5Mohammed Anbar6Michel Makhlouf7Mowafa Househ8College of Science and Engineering, Hamad Bin Khalifa University, Member of Qatar Foundation, Doha, Qatar; Corresponding authorCollege of Science and Engineering, Hamad Bin Khalifa University, Member of Qatar Foundation, Doha, QatarWeil Cornell Medical College-Qatar, Doha, Qatar; Sidra Medical and Research Center, Member of Qatar Foundation, Doha, QatarCollege of Science and Engineering, Hamad Bin Khalifa University, Member of Qatar Foundation, Doha, QatarCollege of Science and Engineering, Hamad Bin Khalifa University, Member of Qatar Foundation, Doha, QatarCollege of Science and Engineering, Hamad Bin Khalifa University, Member of Qatar Foundation, Doha, Qatar; Weil Cornell Medical College-Qatar, Doha, QatarNational Advanced IPv6 Centre, University Sains Malaysia, Penang, MalaysiaSidra Medical and Research Center, Member of Qatar Foundation, Doha, QatarCollege of Science and Engineering, Hamad Bin Khalifa University, Member of Qatar Foundation, Doha, Qatar; Corresponding authorSummary: Several reviews have been conducted regarding artificial intelligence (AI) techniques to improve pregnancy outcomes. But they are not focusing on ultrasound images. This survey aims to explore how AI can assist with fetal growth monitoring via ultrasound image. We reported our findings using the guidelines for PRISMA. We conducted a comprehensive search of eight bibliographic databases. Out of 1269 studies 107 are included. We found that 2D ultrasound images were more popular (88) than 3D and 4D ultrasound images (19). Classification is the most used method (42), followed by segmentation (31), classification integrated with segmentation (16) and other miscellaneous methods such as object-detection, regression, and reinforcement learning (18). The most common areas that gained traction within the pregnancy domain were the fetus head (43), fetus body (31), fetus heart (13), fetus abdomen (10), and the fetus face (10). This survey will promote the development of improved AI models for fetal clinical applications.http://www.sciencedirect.com/science/article/pii/S2589004222009853Health informaticsDiagnostic technique in health technologyMedical imagingArtificial intelligence |
| spellingShingle | Mahmood Alzubaidi Marco Agus Khalid Alyafei Khaled A. Althelaya Uzair Shah Alaa Abd-Alrazaq Mohammed Anbar Michel Makhlouf Mowafa Househ Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images iScience Health informatics Diagnostic technique in health technology Medical imaging Artificial intelligence |
| title | Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images |
| title_full | Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images |
| title_fullStr | Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images |
| title_full_unstemmed | Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images |
| title_short | Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images |
| title_sort | toward deep observation a systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images |
| topic | Health informatics Diagnostic technique in health technology Medical imaging Artificial intelligence |
| url | http://www.sciencedirect.com/science/article/pii/S2589004222009853 |
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