Medical Instrument Detection in Ultrasound-Guided Interventions: A Review
It addresses the problem of improving surgical efficiency and outcomes in computer-assisted interventions for medical professionals, but it is incremental as it is a review paper.
This article reviews methods for detecting medical instruments in ultrasound-guided interventions, covering both traditional non-data-driven and modern data-driven approaches, and discusses clinical applications such as anesthesia and biopsy validated on clinical datasets.
Medical instrument detection is essential for computer-assisted interventions since it would facilitate the surgeons to find the instrument efficiently with a better interpretation, which leads to a better outcome. This article reviews medical instrument detection methods in the ultrasound-guided intervention. First, we present a comprehensive review of instrument detection methodologies, which include traditional non-data-driven methods and data-driven methods. The non-data-driven methods were extensively studied prior to the era of machine learning, i.e. data-driven approaches. We discuss the main clinical applications of medical instrument detection in ultrasound, including anesthesia, biopsy, prostate brachytherapy, and cardiac catheterization, which were validated on clinical datasets. Finally, we selected several principal publications to summarize the key issues and potential research directions for the computer-assisted intervention community.