Application of Artificial Intelligence Deep Learning Technology in Magnetic Resonance Lumbar Imaging
September 7, 2023 updated by: RenJi Hospital
To study the comparative analysis of artificial intelligence deep learning technology in the image quality of under-artificial intelligence (AI) reconstruction images and the original acquisition images of magnetic resonance lumbar spine
Study Overview
Status
Not yet recruiting
Intervention / Treatment
Study Type
Observational
Enrollment (Estimated)
40
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Yes
Sampling Method
Non-Probability Sample
Study Population
Patients of both sexes, aged ≥18 years, with no history of lumbar surgery, underwent lumbar magnetic resonance imaging examination.
Description
Inclusion Criteria:
- Patients of both sexes, aged ≥18 years, with no history of lumbar surgery, underwent lumbar magnetic resonance imaging examination.
Exclusion Criteria:
- With metal implants in the body, claustrophobic, unable to lie flat for 15 minutes, with a history of lumbar surgery.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Application of Artificial Intelligence Deep Learning Technology in Magnetic Resonance Lumbar Imaging
Time Frame: 2025.3-2025.6
|
manuscript
|
2025.3-2025.6
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
October 8, 2023
Primary Completion (Estimated)
March 8, 2024
Study Completion (Estimated)
March 8, 2024
Study Registration Dates
First Submitted
September 7, 2023
First Submitted That Met QC Criteria
September 7, 2023
First Posted (Actual)
September 14, 2023
Study Record Updates
Last Update Posted (Actual)
September 14, 2023
Last Update Submitted That Met QC Criteria
September 7, 2023
Last Verified
September 1, 2023
More Information
Terms related to this study
Other Study ID Numbers
- LY2023-121-B
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.