This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences).

This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.

本期特刊侧重于在多个学科和各个应用领域的一系列贡献中的协同断层扫描图像重建。图像重建的主题涵盖了大量的逆问题（数学），这些问题通过各种方法解决，包括统计方法（例如贝叶斯方法、蒙特卡洛）和计算方法（例如机器学习、计算建模、模拟）。该问题分为两卷。本卷主要关注算法和方法。一些文章将展示它们在现实世界挑战中的实用性，无论是医学应用（例如心血管疾病、质子治疗计划）还是材料科学中的应用（例如材料分解和表征）。

本文是主题问题“协同断层图像重建：第 1 部分”的一部分。