Evaluating the Efficacy of Deep Learning Reconstruction in Reducing Radiation Dose for Computer-Aided Volumetry for Liver Tumor: A Phantom Study
Findings of our phantom study show that reconstruction method had influence on CAD v merits for abdominal CT with not only standard but also reduced dose examinations and that DLR can potentially yield better image quality and CAD v measurements than FBP, hybrid-type IR, or MBIR in this setting.
Authors
- Daisuke Takenaka (ORCID: https://orcid.org/0000-0002-9432-7180)
- Naruomi Akino (ORCID: https://orcid.org/0000-0002-7413-2095)
- Hirona Kimata
- Takeshi Yoshikawa (ORCID: https://orcid.org/0000-0001-5560-5371)
- Hiroyuki Nagata (ORCID: https://orcid.org/0000-0001-7998-955X)
- Yoshiharu Ohno (ORCID: https://orcid.org/0000-0002-4431-1084)
- Yuya Ito (ORCID: https://orcid.org/0000-0002-1292-3166)
- Takahiro Ueda (ORCID: https://orcid.org/0000-0003-2577-3619)
- Kenji Fujii (ORCID: https://orcid.org/0000-0001-6603-6362)
- Yoshiyuki Ozawa (ORCID: https://orcid.org/0000-0002-8252-1947)
- Masahiko Nomura
Institutions
- Canon (Japan) (JP)
- Fujita Health University (JP)
- Fujita Health University Hospital (JP)
- Research Organization of Information and Systems (JP)
- Hyogo Prefectural Cancer Center (JP)
- Canon Medical Systems Corporation (Japan) (JP)
Publication Details
- Journal
- Journal of Computer Assisted Tomography
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1097/rct.0000000000001657
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00