Cone beam computed tomography (CBCT) is an imaging modality that has been used in image-guided radiation therapy (IGRT). For applications such as lung radiation therapy, CBCT images are greatly affected by the motion artefacts. This is mainly due to low temporal resolution of CBCT. Recently, a dual modality of electrical impedance tomography (EIT) and CBCT has been proposed, in which the high temporal resolution EIT imaging system provides motion data to a motion-compensated algebraic reconstruction technique (ART)-based CBCT reconstruction software. High computational time associated with ART and indeed other variations of ART make it less practical for real applications. This paper develops a motion-compensated conjugate gradient least-squares (CGLS) algorithm for CBCT. A motion-compensated CGLS offers several advantages over ART-based methods, including possibilities for explicit regularization, rapid convergence and parallel computations. This paper for the first time demonstrates motion-compensated CBCT reconstruction using CGLS and reconstruction results are shown in limited data CBCT considering only a quarter of the full dataset. The proposed algorithm is tested using simulated motion data in generic motion-compensated CBCT as well as measured EIT data in dual EIT–CBCT imaging.
|Journal||Philosophical Transactions of the Royal Society A - Mathematical Physical and Engineering Sciences|
|Early online date||4 May 2015|
|Publication status||Published - Jun 2015|
- Cone beam computed tomography
- Conjugate gradient least squares
- Dual modality imaging
- Electrical impedance tomography
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- Department of Electronic & Electrical Engineering - Professor
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Biosensors, Bioelectronics and Biodevices (C3Bio)
- Centre for Autonomous Robotics (CENTAUR)
- Electronics Materials, Circuits & Systems Research Unit (EMaCS)
Person: Research & Teaching