Improving ultrasound image quality during early pregnancy using AI
Official title: Deep Learning-based Quality Control of Ultrasound Images During Early Pregnancy
Run by Chinese Academy of Sciences · NCT06002412 · Data updated 2026-11-12
This study is testing if using artificial intelligence can improve the quality of ultrasound images during early pregnancy to help doctors better identify important fetal features and reduce misdiagnoses.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 20 Years and up |
| Sex | Women only |
| Enrollment | 400 (estimated) |
| Sponsor | Chinese Academy of Sciences Government |
| Locations | 4 sites (Beijing and 3 other locations) |
| Status | Recruiting |
| Started | September 1, 2023 |
| Main results expected | December 31, 2023 |
| Study ends | July 30, 2028 |
| Registry record updated | September 8, 2023 |
| Trial ID | NCT06002412 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are women in early pregnancy who have clear ultrasound images showing specific fetal views.
✕Probably not a fit
Patients who are in mid to late pregnancy or have unclear ultrasound images will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This research integrates artificial intelligence to enhance the quality control of ultrasound images during early pregnancy, focusing on specific fetal anatomical sections. Collaborating with prominent medical institutions, the study collects extensive fetal ultrasound data to develop a deep learning model. This model aims to accurately identify key anatomical areas in ultrasound images and assess their quality in real-time. By ensuring high-quality imaging, the tool is expected to significantly reduce misdiagnoses of conditions such as Down Syndrome and neural system deformities.
Why it matters
Potential benefit: If successful, this approach could lead to more accurate diagnoses and improved outcomes for pregnancies by reducing the rates of missed fetal abnormalities.
How similar studies have gone: Other studies have shown promise in using AI for image analysis, indicating potential success for this novel approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Women in early pregnancy who have detailed personal information and ultrasound images. * The ultrasound images should clearly show the fetus's median sagittal, NT, and choroid plexus views. Exclusion Criteria: * Ultrasound images from women in mid to late pregnancy. * Ultrasound images that are unclear or blurry, making evaluation difficult. * Women who did not provide complete personal and medical information during the ultrasound scan.
Where it's running
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Beijing Obstetrics and Gynecology Hospital affiliated to Capital Medical University
Beijing, China Recruiting -
Peking University Third Hospital
Beijing, China Recruiting -
Changsha Hospital for Maternal and Child Health Care
Changsha, China Recruiting -
Second Xiangya Hospital of Central South University
Changsha, China Recruiting
Study contacts
- Study coordinator: Di Dong, Ph.D
- Email: di.dong@ia.ac.cn
- Phone: +86 13811833760
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
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EARLY-PREG: Mapping maternal–embryo molecular communication before and after conception
This project will test whether patterns of proteins and other molecules in maternal fluids change in the first two weeks after fertilization in healthy women trying to conceive and in women not seeking pregnancy.
-
Texting AI support for early pregnancy care in Philadelphia
This project will test whether a texting conversational AI (CIRCA) can recruit and support people in early pregnancy in the Philadelphia area.
-
Early lifestyle program for pregnant women with mildly high early-pregnancy blood sugar
This program tests whether starting diet, exercise, weight management and home blood‑glucose monitoring early in pregnancy helps women with mildly high early-pregnancy blood sugar have fewer large babies and preterm births.
How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.