Improving ultrasonic image analysis with advanced algorithms
Intelligent Segmentation Algorithm of Ultrasonic Image
This study is testing new computer programs to see if they can make ultrasound images clearer and help doctors better identify important features in those images.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 5000 (estimated) |
| Sex | All |
| Sponsor | Tongji Hospital Academic / other |
| Locations | 1 site (Wuhan, Hubei) |
| Trial ID | NCT06646679 on ClinicalTrials.gov |
What this trial studies
This project focuses on enhancing ultrasonic image analysis by optimizing neural network algorithms and constructing extensive datasets for ultrasonic imagery. The study involves developing high-performance algorithms for image recognition and segmentation, which will be trained and evaluated using a data-driven approach. The results aim to facilitate accurate segmentation of regional block images and improve the identification of characteristic ultrasonic anatomy, ultimately advancing ultrasonic technology.
Who should consider this trial
Good fit: Ideal candidates for this study include individuals undergoing ultrasonic imaging procedures.
Not a fit: Patients who do not require ultrasonic imaging or have contraindications for such procedures may not benefit from this study.
Why it matters
Potential benefit: If successful, this could lead to more accurate and efficient ultrasonic imaging techniques for patients.
How similar studies have performed: Other studies have shown success in improving imaging techniques through algorithm optimization, indicating potential for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * None. Exclusion Criteria: * None.
Where this trial is running
Wuhan, Hubei
- Tianzhu Liu — Wuhan, Hubei, China (Recruiting)
Study contacts
- Principal investigator: Mei Wei, M.D. — Tongji Hospital
- Study coordinator: Liu Tianzhu, M.D.
- Email: liutzh@126.com
- Phone: 13098866448
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.