Unique ID issued by UMIN | UMIN000030721 |
---|---|
Receipt number | R000035076 |
Scientific Title | Automatic detection of acute brain infarction |
Date of disclosure of the study information | 2018/03/01 |
Last modified on | 2021/01/11 12:38:31 |
Automatic detection of acute brain infarction
Automatic detection of acute brain infarction
Automatic detection of acute brain infarction
Automatic detection of acute brain infarction
Japan |
acute brain infarction
Neurology | Radiology | Neurosurgery |
Emergency medicine | Adult |
Others
NO
To detect abnormal signal intensity on diffusion weighted images of brain MRI by using statistical approach
Efficacy
Detection of abnormal signal intensity on DWI
Observational
Not applicable |
Not applicable |
Male and Female
Patients who underwent brain DWI
Images with severe artifacts
1000
1st name | Yasutaka |
Middle name | |
Last name | Fushimi |
Kyoto University Graduate School of Medicine
Department of Diagnostic Imaging and Nuclear Medicine
6068507
54 Shogoin Kawaharacho, Sakyoku, Kyoto JAPAN
075-751-3760
nmdioffice@kuhp.kyoto-u.ac.jp
1st name | Yasutaka |
Middle name | |
Last name | Fushimi |
Kyoto University Graduate School of Medicine
Department of Diagnostic Imaging and Nuclear Medicine
6068607
54 Shogoin Kawaharacho, Sakyoku, Kyoto JAPAN
075-751-3760
yfushimi@kuhp.kyoto-u.ac.jp
Kyoto University
Ministry of Education, Culture, Sports, Science and Technology
Japanese Governmental office
Kyoto University Graduate School and Faculty of Medicine, Ethics Committee
Yoshida-Konoe-cho, Sakyo-ku, Kyoto 606-8501, JAPAN
075-753-4680
ethcom@kuhp.kyoto-u.ac.jp
NO
2018 | Year | 03 | Month | 01 | Day |
Unpublished
Open public recruiting
2018 | Year | 01 | Month | 01 | Day |
2018 | Year | 03 | Month | 27 | Day |
2018 | Year | 03 | Month | 27 | Day |
2023 | Year | 03 | Month | 26 | Day |
N/A
2018 | Year | 01 | Month | 08 | Day |
2021 | Year | 01 | Month | 11 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000035076