Emerging Trends in AI, Ultrasound and OB/GYN Care

Given the influx of artificial intelligence (AI)-powered tools in health care, this author examines the potential intersection of this technology and ultrasound examination in obstetrics and gynecologic (OB/GYN) care

From entertainment to commerce, artificial intelligence (AI) is making a difference in many aspects of life and has the power to advance diagnostics. Next-generation healthcare technology has begun implementing many AI-powered tools to improve efficacy and patient safety, and enhance the clinician experience.1

There are several image acquisition and analysis capabilities that can be enhanced by an AI application for each task.2 These capabilities include:

• Classification – identifying objects that are present in the scan

• Segmentation – locating organ boundaries

• Navigation – visualizing how to best acquire an optimal scan

• Quality assessment – determining if a diagnosis can be made based on the scan

• Diagnosis – reviewing what is wrong with the imaged object

Nearly every woman requires an ultrasound at some point during their care. There is huge potential for AI to assist in repetitive tasks and provide promising workload-changing advances with the use of ultrasound in obstetrics and gynecologic (OB/GYN) care.2

Can AI Have an Impact in OB/GYN Care?

According to research published in Ultrasound in Obstetrics and Gynecology, AI has had little impact on the field of OB/GYN thus far.2 However, it is on track to make waves within the sector. Recently there’s been a push for collaboration between AI developers and ultrasound professionals.2 Medical device companies have listened to this call to action and have begun innovating and implementing AI technology within ultrasound solutions for women’s health.

It is critical to monitor and observe fetal growth and development throughout pregnancy. Ultrasound examination is one method of tracking these changes.3 One of the conditions that clinicians monitor for is congenital heart disease (CHD), which is one of the leading organ-specific birth defects as well as the leading cause of infant morbidity and mortality from congenital malformations. In regard to prenatal detection of CHD, two-dimensional sonography delivers low levels of accuracy – only 15 to 39 percent – due to the complex anatomy and small size of the fetal heart.4

To address this, tools and solutions using AI have been developed to enhance visualization and allow physicians to provide a CHD diagnosis more accurately.4 One tool, known as Fetal Intelligent Navigation Echocardiography (FINE), integrates spatiotemporal image correlation volume data sets using “intelligent navigation” technology to simplify fetal cardiac examinations and reduce operator dependency.

Researchers have investigated FINE over the past several years to determine accuracy. In a 2020 publication, Yeo and Romero found that FINE:

• Helps healthcare providers assess both normal and abnormal fetal hearts.

• Can automatically provide nine standard fetal echocardiography views in 96 to 100 percent of normal fetal heart cases.

• Can provide clinically useful information about cardiac structure and function in both normal and abnormal fetal hearts when color Doppler is activated.

• Has high sensitivity (98 percent) and specificity (93 percent) for the detection of CHD.4

FINE technology, which is exclusively known as 5D Heart™ on Samsung ultrasound systems, was created to provide high-quality prenatal screening and diagnosis of CHD to clinicians and pregnant mothers.4

Since obstetric ultrasound is time-consuming, the use of AI may also reduce exam time and improve workflow.3 Working in very fast-paced environments, clinicians are looking for accuracy and speed in diagnostic tools. From administrative workflow to clinical documentation and patient outreach, AI can help with all aspects of the diagnostic process.1

What The Future Holds for AI and Ultrasound Imaging

Experts and research trends continue to show how AI will revolutionize the medical imaging sector in the future. One recent study published in the National Library of Medicine estimated that AI applications have the potential to cut annual U.S. healthcare costs by $150 billion in 2026.1

Some worry that AI algorithms will replace health-care providers but they will actually act as clinical support tools. By working in tandem with AI algorithms, physicians can better ensure that tests are performed accurately, and the correct diagnosis is reached. To improve patient care and reduce costs, we must encourage and provide support for providers to learn more about AI applications and fully engage them in practice. We expect to continue seeing new and updated AI tools to stay at the forefront of the imaging sector and OB/GYN care.


1. Bohr A, Memarzadeh K. The rise of artificial intelligence in healthcare applications. National Library of Medicine. 2020;25-60. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325854/ . Published June 26, 2020. Accessed September 20, 2022.

2. Drukker L, Noble JA, Papageorghiou AT. Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology. Ultrasound Obstet Gynecol. 2020;56(4):498-505.

3. Chen Z, Liu Z, Du M, Wang Z Artificial intelligence in obstetric ultrasound: an update and future applications. Front Med (Lausanne). Available at: https://www.frontiersin.org/articles/10.3389/fmed.2021.733468/full . Published August 27, 2021. Accessed September 20, 2022.

4. Yeo L, Romero R. New and advanced features of fetal intelligent navigation echocardiography (FINE) or 5D heart. J Matern Fetal Neonatal Med. 2022;35(8):1498-1516.