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Method for image equalization of ROI fluoroscopic images using mask localization, selection and subtraction
L M Fletcher1, S Rudin, D R Bednarek
1Department of Biophysical Sciences, State University of New York at Buffalo, School of Medicine and Biomedical Sciences 14215, USA.
Summary
This study introduces a new method for region of interest (ROI) fluoroscopy, reducing X-ray dose and equalizing image brightness using optimized ROI search and mask subtraction. The technique successfully reduced radiation exposure and improved image quality in phantom studies.
Area of Science:
- Medical Imaging
- Radiology
- Image Processing
Background:
- Fluoroscopy involves significant X-ray dose to patients, especially in peripheral regions.
- Maintaining consistent image brightness across regions of interest (ROI) and the periphery is challenging.
Purpose of the Study:
- To develop and validate an optimized method for region of interest (ROI) fluoroscopy.
- To reduce patient X-ray dose while ensuring uniform image brightness.
Main Methods:
- Utilized a filter to reduce X-ray dose to the patient periphery.
- Implemented mask subtraction with a descriptor look-up table (DLUT) for ROI localization and mask selection.
- DLUT considered ROI size, relative brightness, shape, and orientation.
Main Results:
- Successfully equalized displayed image brightness between ROI and periphery after mask subtraction.
- Validated the method on 50 fluoroscopic images of anthropomorphic phantoms.
- Simulated the methodology for real-time applications in PC code.
Conclusions:
- The developed methodology effectively reduces X-ray dose in ROI fluoroscopy.
- Achieved comparable brightness levels between ROI and periphery for improved visualization.
- Real-time implementation is feasible and currently in progress.