Deep Reinforcement Learning for Optimizing Angle Selection and Dose Allocation in CT Reconstruction

arXiv (Cornell University)

Abstract

Traditional X-ray computed tomography (CT) scanning strategies typically select projection angles uniformly and allocate dose equally. In practice, however, CT scans often need to be fast, radiation-efficient, and adaptive. Sparse-view tomography addresses these requirements by reducing both the number of angles and the total dose budget. Under such constraints, angle selection and dose allocation should be information-driven, with more dose assigned to informative directions. To this end, we propose a dose-aware acquisition and reconstruction framework that combines a PWLS-PnP reconstruction backbone with an RL-based strategy for adaptive angle selection, explicitly accounting for angle-dependent photon statistics. Numerical experiments show that the proposed approach improves overall reconstruction quality and enhances defect detectability compared with conventional strategies, particularly when only a small number of projections or a constrained dose budget is available.

Authors 5

1. Tianyuan Wang Aachen Leiden Institute of Advanced Computer Science

   Leiden University · Centrum Wiskunde & Informatica

   Affiliation as printed

   Centrum Wiskunde & Informatica , Science Park 123 , Amsterdam , 1098 XG , The Netherlands

   Leiden Institute of Advanced Computer Science , Leiden Universiteit , Leiden , The Netherlands

2. Daniel M. Pelt Aachen Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden Institute of Advanced Computer Science , Leiden Universiteit , Leiden , The Netherlands

3. Felix Lucka

   Centrum Wiskunde & Informatica

   Affiliation as printed

   Centrum Wiskunde & Informatica , Science Park 123 , Amsterdam , 1098 XG , The Netherlands

4. Tristan van Leeuwen

   Centrum Wiskunde & Informatica · Utrecht University

   Affiliation as printed

   Centrum Wiskunde & Informatica , Science Park 123 , Amsterdam , 1098 XG , The Netherlands

   Mathematics Institute , Utrecht University , Campus-Boulevard 30 , Utrecht , 3584 CD , The Netherlands

5. K. Joost Batenburg Aachen Leiden Institute of Advanced Computer Science

   Leiden University · Centrum Wiskunde & Informatica

   Affiliation as printed

   Centrum Wiskunde & Informatica , Science Park 123 , Amsterdam , 1098 XG , The Netherlands

   Leiden Institute of Advanced Computer Science , Leiden Universiteit , Leiden , The Netherlands