Reproducibility is a cornerstone of science, as the replication of findings is the process through which they become knowledge. It is widely considered that many fields of science are undergoing a reproducibility crisis. This has led to the publications of various guidelines in order to improve research reproducibility. This didactic chapter intends at being an introduction to reproducibility for researchers in the field of machine learning for medical imaging. We first distinguish between different types of reproducibility. For each of them, we aim at defining it, at describing the requirements to achieve it and at discussing its utility. The chapter ends with a discussion on the benefits of reproducibility and with a plea for a non-dogmatic approach to this concept and its implementation in research practice.

翻译：复制是科学的基石,因为复制研究成果是它们成为知识的过程,人们普遍认为,许多科学领域正在经历一种可复制的危机,因此出版了各种准则,以改进研究的可复制性,这个实用章节旨在介绍研究人员在医学成像的机器学习领域的可复制性,我们首先区分不同类型的可复制性,我们针对其中每一种类型,目的是界定它,说明实现它的要求,并讨论其效用,最后讨论可复制性的好处,呼吁对这一概念采取非教条性做法,并在研究实践中加以实施。