Noise reduction in magnetic resonance imaging by deep learning image reconstruction

Noise reduction in magnetic resonance imaging by deep learning image reconstruction - Noise reduction in magnetic resonance imaging

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000036700

Enrollment

680

Registered

2019-08-19

Start date

2019-08-01

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

MRI data obtained for berain, optic nearve, spine/bone/joint, breast and heart

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1. Twenty years old or more at the time of informed consent 2. Signed informed consent is obtained from the participant or his/her representative 3. MRI of the target body area of the present clinical study is planned to be performed

Exclusion criteria

Exclusion criteria: 1. When MRI data are regarded as inappropriate for evaluation by the investigators because of the image degradation by body movement during data aquisition and other reasons 2. Those who cannot understand the explanation of the research content

Design outcomes

Primary

Measure	Time frame
MRI images reconstructed by deep learning image reconstruction and those by conventional image reconstruction	—

Countries

Japan

Contacts

Public ContactTsuneo Saga

Graduate School of Medicine, Kyoto University Department of Advanced Medical Imaging Research

saga@kuhp.kyoto-u.ac.jp075-751-3544

Outcome results