As computer vision algorithms increase in capability, their applications in clinical systems will become more pervasive. These applications include: diagnostics, such as colonoscopy and bronchoscopy; guiding biopsies, minimally invasive interventions, and surgery; automating instrument motion; and providing image guidance using pre-operative scans. Many of these applications depend on the specific visual nature of medical scenes and require designing algorithms to perform in this environment. In this review, we provide an update to the field of camera-based tracking and scene mapping in surgery and diagnostics in medical computer vision. We begin with describing our review process, which results in a final list of 515 papers that we cover. We then give a high-level summary of the state of the art and provide relevant background for those who need tracking and mapping for their clinical applications. After which, we review datasets provided in the field and the clinical needs that motivate their design. Then, we delve into the algorithmic side, and summarize recent developments. This summary should be especially useful for algorithm designers and to those looking to understand the capability of off-the-shelf methods. We maintain focus on algorithms for deformable environments while also reviewing the essential building blocks in rigid tracking and mapping since there is a large amount of crossover in methods. With the field summarized, we discuss the current state of the tracking and mapping methods along with needs for future algorithms, needs for quantification, and the viability of clinical applications. We then provide some research directions and questions. We conclude that new methods need to be designed or combined to support clinical applications in deformable environments, and more focus needs to be put into collecting datasets for training and evaluation.

翻译：随着计算机视觉算法能力的提升，其在临床系统中的应用将日益广泛。这些应用包括：诊断领域（如结肠镜检查和支气管镜检查）、引导活检与微创介入手术、自动化器械运动控制，以及利用术前影像提供导航辅助。其中许多应用依赖于医学场景的特殊视觉特性，需要设计在该环境中运行的算法。本综述对医学计算机视觉领域中基于摄像头的追踪与场景映射技术在外科手术及诊断方面的最新进展进行了更新。我们首先阐述文献筛选流程，最终纳入515篇论文。随后对现有技术进行宏观概括，并为需要将追踪与映射技术用于临床应用的读者提供相关背景知识。在此基础上，我们回顾了该领域公开的数据集及其设计的临床需求驱动因素，继而深入算法层面，总结最新研究成果。该总结对算法设计者以及希望了解现成方法能力的读者尤为有用。我们重点关注形变环境下的算法，同时梳理刚性追踪与映射中的关键基础模块——鉴于两类方法存在大量技术交叉。在完成领域总结后，我们探讨了追踪与映射方法的现状，涵盖未来算法需求、量化评估需求及临床应用的可行性。最后提出若干研究方向与待解决问题。结论认为：需要设计或组合新方法以支持形变环境下的临床应用，同时应更注重用于训练与评估的数据集采集工作。