Abstract
We develop a mathematical framework for the design of orbital trajectories that are optimal to a particular imaging task (or tasks) in advanced cone-beam computed tomography systems that have the capability of general source-detector positioning. The framework allows various parameterizations of the orbit as well as constraints based on imaging system capabilities. To accommodate nonstandard system geometries, a modelbased iterative reconstruction method is applied. Such algorithms generally complicate the assessment and prediction of reconstructed image properties; however, we leverage efficient implementations of analytical predictors of local noise and spatial resolution that incorporate dependencies of the reconstruction algorithm on patient anatomy, x-ray technique, and geometry. These image property predictors serve as inputs to a taskbased performance metric defined by detectability index, which is optimized with respect to the orbital parameters of data acquisition. We investigate the framework of the task-driven trajectory design in several examples to examine the dependence of optimal source-detector trajectories on the imaging task (or tasks), including location and spatial-frequency dependence. A variety of multitask objectives are also investigated, and the advantages to imaging performance are quantified in simulation studies.
Original language | English (US) |
---|---|
Article number | 025002 |
Journal | Journal of Medical Imaging |
Volume | 6 |
Issue number | 2 |
DOIs | |
State | Published - Apr 1 2019 |
Keywords
- Cone-beam computed tomography
- Detectability index
- Image quality
- Imaging task
- Interventional imaging
- Model-based image reconstruction
- Optimization
- Robotic C-arm
- Task function
- Task-driven imaging
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging