Developing a system to improve echocardiography image quality using deep learning
Echocardiography Image Quality Management System Based on Deep Learning: A Single-center Prospective Study
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School · NCT05633732
This study is testing a new system that uses deep learning to improve the quality of heart ultrasound images for patients getting echocardiograms.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 2000 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School (other) |
| Locations | 1 site (Nanjing, Jiangsu) |
| Trial ID | NCT05633732 on ClinicalTrials.gov |
What this trial studies
This study aims to create an echocardiography image quality management system that utilizes deep learning techniques for automatic and objective quality control of echocardiography images. A total of 2000 patients undergoing transthoracic echocardiography will be enrolled, with data from 1500 patients used for training the system and the remaining for validation. The study will analyze various echocardiography views and employ advanced video processing models to assess image quality. The goal is to enhance the accuracy and reliability of echocardiography assessments.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who can provide standardized transthoracic echocardiography views.
Not a fit: Patients with incomplete standard TTE views or poor sound transmission conditions may not benefit from this study.
Why it matters
Potential benefit: If successful, this system could significantly improve the quality and consistency of echocardiography images, leading to better patient outcomes.
How similar studies have performed: While the use of deep learning in medical imaging is gaining traction, this specific approach to echocardiography image quality management is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. aged ≥18years, gender unlimited; 2. Patients with standardized TTE views; 3. Subjects participated in the study voluntarily and signed informed consent; Exclusion Criteria: 1. patients wirh incomplete standard TTE views; 2. patients with poor sound transmission conditions.
Where this trial is running
Nanjing, Jiangsu
- Affiliated Drum Tower Hospital of Nanjing University Medical School — Nanjing, Jiangsu, China (RECRUITING)
Study contacts
- Study coordinator: Jing Yao, Phd
- Email: w1835199709@163.com
- Phone: +8618905188727
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.
Conditions: Echocardiography, Quality Management System, Deep learning, Artificial Intelligence