UMIN ID: UMIN000052031
Registered date:01/09/2023
Image quality evaluation of MRI images by denoising reconstruction technology using deep learning
Basic Information
| Recruitment status | Pending |
|---|---|
| Health condition(s) or Problem(s) studied | volunteer |
| Date of first enrollment | 2023/09/01 |
| Target sample size | 30 |
| Countries of recruitment | Japan |
| Study type | Interventional |
| Intervention(s) | Participation period is only at the time of MRI imaging. MRI takes about 15 minutes. |
Outcome(s)
| Primary Outcome | It is expected to reduce inspection time while maintaining the same image quality as conventional imaging conditions, improve image quality by improving resolution, and reduce motion artifacts. |
|---|---|
| Secondary Outcome |
Key inclusion & exclusion criteria
| Age minimum | 20years-old |
|---|---|
| Age maximum | 65years-old |
| Gender | Male and Female |
| Include criteria | |
| Exclude criteria | 1) People with pacemakers or tattoos that are contraindicated for MR examinations 2) Pregnant women 3) People with claustrophobia |
Related Information
| Primary Sponsor | St.Marianna University Hospital Department of Radiological Technology |
|---|---|
| Secondary Sponsor | |
| Source(s) of Monetary Support | St.Marianna University Hospital Department of Radiological Technology |
| Secondary ID(s) |
Contact
| public contact | |
| Name | yuki deguchi |
| Address | 2-16-1 Sugao, Miyamae Ward, Kawasaki City, Kanagawa Prefecture Japan 2168511 |
| Telephone | 0449778111 |
| y.deguchi0418@marianna-u.ac.jp | |
| Affiliation | St.Marianna University Hospital Department of Radiological Technology |
| scientific contact | |
| Name | yuki deguchi |
| Address | 2-16-1 Sugao, Miyamae Ward, Kawasaki City, Kanagawa Prefecture Japan |
| Telephone | 0449778111 |
| y.deguchi0418@marianna-u.ac.jp | |
| Affiliation | St.Marianna University Hospital Department of Radiological Technology |