Dr. Ander Biguri Profile

Dr. Ander Biguri

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Publications (1)

Proceedings Article | 29 March 2024 Poster + Paper

Source-detector trajectory optimization for customized CBCT field of view extension using simulated annealing algorithm

Hannah Jungreuthmayer, S. M. Ragib Shahriar Islam, Ander Biguri, Gernot Kronreif, Wolfgang Birkfellner, Sepideh Hatamikia

Proceedings Volume 12928, 129281S (2024) https://doi.org/10.1117/12.3006176

KEYWORDS: Mathematical optimization, Cone beam computed tomography, Kinematics, Image quality, Algorithms, Image quality standards, Visualization, Tomography

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Cone Beam CT (CBCT) has become a routine clinical imaging modality in interventional radiology. Extended Field of View (FOV) CBCT is of great clinical importance for many medical applications, especially for cases where the Volume of Interest (VOI) is outside the standard FOV. In this study, we investigate FOV extension by optimizing customized source-detector CBCT trajectories using Simulated Annealing (SA) algorithm, a heuristic search optimization algorithm. The SA algorithm explores different elliptical trajectories within a given parameter space, attempting to optimize image quality in a given VOI. Kinematic constraints (e.g., due to collisions of the imager with the patient or other medical devices) are taken into account when designing the trajectories. For optimization process, a digital XCAT body phantom was used in which three lesions were placed at extreme positions in the phantom that could not be imaged with the standard circular trajectory. The volume around each lesion was considered as VOI. The geometry of Philips Allura Xper C-arm was considered for simulation. Tomographic Iterative GPU-based Reconstruction (TIGRE) and Universal Quality Index (UQI) were used for image reconstruction and image quality assessment, respectively. Our results showed that proposed trajectories could achieve a UQI of 0.9148, 0.9681, and 0.9632 at the respective three VOIs, which was significantly better image quality compared with circular trajectory (0.5960, 0.4892, and 0.4798 for the three VOIs). In addition, the FOV extension achieved for the three optimized source-detector trajectories was 28.75%, 23.57%, and 22.49%, respectively. Our experimental results have shown that our proposed customized trajectories can lead to an extended FOV and enable improved visualization of anatomical structures in extreme positions while taking into account the available kinematic constraints. This study offers a new approach to improve the diagnostic capabilities of CBCT imaging, thus providing valuable insight into improving patient care in CBCT imaging.

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