Edge Projection-Based Adaptive View Selection for Cone-Beam CT
| Autor: | Lin, Jingsong, Venkatakrishnan, Singanallur, Buzzard, Gregery, Ziabari, Amir Koushyar, Bouman, Charles |
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| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | Industrial cone-beam X-ray computed tomography (CT) scans of additively manufactured components produce a 3D reconstruction from projection measurements acquired at multiple predetermined rotation angles of the component about a single axis. Typically, a large number of projections are required to achieve a high-quality reconstruction, a process that can span several hours or days depending on the part size, material composition, and desired resolution. This paper introduces a novel real-time system designed to optimize the scanning process by intelligently selecting the best next angle based on the object's geometry and computer-aided design (CAD) model. This selection process strategically balances the need for measurements aligned with the part's long edges against the need for maintaining a diverse set of overall measurements. Through simulations, we demonstrate that our algorithm significantly reduces the number of projections needed to achieve high-quality reconstructions compared to traditional methods. Comment: Submitted to 2024 Asilomar Conference on Signals, Systems, and Computers |
| Databáze: | arXiv |
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