Abstract
CT diagnostic imaging is a major contributor to ionizing radiation exposure in the United States. Unfortunately, a reduction in radiation dose often results in degraded image quality. Automatic Exposure Control (AEC) is the most commonly used method to balance image quality and dose in x-ray CT, generally by modifying the scan's tube current modulation (TCM) parameters. To allow current AEC techniques to be better personalized to the patient size, organ dose, and clinical task, our team previously proposed Scout-Dose and Scout-IQA to prospectively estimate dose and noise from frontal and lateral scouts, scan range, and TCM map. In this study, we evaluate for the first time the performance of our scout-based organ dose and noise predictions in an optimization framework to prospectively determine real-time, personalized TCM maps from a patient's acquired scouts and scan ranges.
Original language | English |
---|---|
Title of host publication | Medical Imaging 2024 |
Subtitle of host publication | Physics of Medical Imaging |
Editors | Rebecca Fahrig, John M. Sabol, Ke Li |
ISBN (Electronic) | 9781510671546 |
DOIs | |
State | Published - 2024 |
Event | Medical Imaging 2024: Physics of Medical Imaging - San Diego, United States Duration: Feb 19 2024 → Feb 22 2024 |
Publication series
Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
---|---|
Volume | 12925 |
ISSN (Print) | 1605-7422 |
Conference
Conference | Medical Imaging 2024: Physics of Medical Imaging |
---|---|
Country/Territory | United States |
City | San Diego |
Period | 2/19/24 → 2/22/24 |
Bibliographical note
Publisher Copyright:© 2024 SPIE.
Funding
This work was supported by GE HealthCare.
Funders | Funder number |
---|---|
GE Healthcare |
Keywords
- deep learning
- dose reduction
- image quality
- optimization
- tube current modulation
- X-ray CT
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Atomic and Molecular Physics, and Optics
- Biomaterials
- Radiology Nuclear Medicine and imaging