Unique ID issued by UMIN | UMIN000037471 |
---|---|
Receipt number | R000042681 |
Scientific Title | Feasibility of deep learning reconstruction in abdominal CT: Optimization and validation |
Date of disclosure of the study information | 2020/04/02 |
Last modified on | 2025/01/27 07:23:12 |
Feasibility of deep learning reconstruction in abdominal CT: Optimization and validation
Feasibility of deep learning reconstruction in abdominal CT: Optimization and validation
Feasibility of deep learning reconstruction in abdominal CT: Optimization and validation
Feasibility of deep learning reconstruction in abdominal CT: Optimization and validation
Japan |
Patients with abnormal laboratory test results or upper abdominal symptoms that raised suspicions of abdominal malignancy underwent dynamic CT.
Radiology |
Malignancy
NO
To investigate whether an iterative reconstruction algorithm and a deep learning reconstruction algorithm improves the image quality in abdominal CT
Efficacy
Objective assessment of image quality
Observational
18 | years-old | <= |
90 | years-old | >= |
Male and Female
Our inclusion criteria were history or suspicion of abdominal tumor, such as hepatocellular carcinoma, cholangiocellular carcinoma, hemangioma, or metastatic liver tumor.
Our exclusion criteria were as follows:emergency case, history of an adverse reaction to iodinated contrast media, proved or suspected pregnancy, and no history of hepatic surgery, TAE, RFA, or renal surgery.
300
1st name | Akio |
Middle name | |
Last name | Tamura |
Iwate Medical University
Depertment of Radiology
020-8505
19-1, Uchimaru, Morioka
0196515111
a.akahane@gmail.com
1st name | Akio |
Middle name | |
Last name | Tamura |
Iwate Medical University
Depertment of Radiology
020-8505
19-1, Uchimaru, Morioka
0196515111
a.akahane@gmail.com
Iwate Medical University
Iwate Medical University
Other
Japan
Iwate Medical University
19-1, Uchimaru, Morioka
+81196515111
a.akahane@gmail.com
NO
2020 | Year | 04 | Month | 02 | Day |
Unpublished
Enrolling by invitation
2019 | Year | 07 | Month | 24 | Day |
2020 | Year | 10 | Month | 05 | Day |
2020 | Year | 04 | Month | 02 | Day |
2025 | Year | 04 | Month | 01 | Day |
none
2019 | Year | 07 | Month | 24 | Day |
2025 | Year | 01 | Month | 27 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000042681