Edge Projection-Based Adaptive View Selection for Cone-Beam CT

TL;DR

This paper presents a real-time adaptive view selection system for cone-beam CT that reduces the number of projections needed for high-quality 3D reconstructions by intelligently choosing measurement angles based on object geometry.

Contribution

It introduces a novel edge projection-based algorithm that optimizes scan angles in real-time, improving efficiency over traditional fixed-angle methods.

Findings

Significantly reduces the number of projections needed for quality reconstructions

Balances measurements along object edges with diverse sampling

Demonstrates effectiveness through simulation results

Abstract

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.