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Active Ultrasound Pattern Injection System (AUSPIS) for Interventional Tool Guidance
Author(s) -
Xiangming Guo,
Hyun Jae Kang,
Ralph EtienneCummings,
Emad M. Boctor
Publication year - 2014
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0104262
Subject(s) - visualization , computer science , ultrasound , computer vision , artificial intelligence , tracking (education) , medical imaging , medical physics , radiology , medicine , psychology , pedagogy
Accurate tool tracking is a crucial task that directly affects the safety and effectiveness of many interventional medical procedures. Compared to CT and MRI, ultrasound-based tool tracking has many advantages, including low cost, safety, mobility and ease of use. However, surgical tools are poorly visualized in conventional ultrasound images, thus preventing effective tool tracking and guidance. Existing tracking methods have not yet provided a solution that effectively solves the tool visualization and mid-plane localization accuracy problem and fully meets the clinical requirements. In this paper, we present an active ultrasound tracking and guiding system for interventional tools. The main principle of this system is to establish a bi-directional ultrasound communication between the interventional tool and US imaging machine within the tissue. This method enables the interventional tool to generate an active ultrasound field over the original imaging ultrasound signals. By controlling the timing and amplitude of the active ultrasound field, a virtual pattern can be directly injected into the US machine B mode display. In this work, we introduce the time and frequency modulation, mid-plane detection, and arbitrary pattern injection methods. The implementation of these methods further improves the target visualization and guiding accuracy, and expands the system application beyond simple tool tracking. We performed ex vitro and in vivo experiments, showing significant improvements of tool visualization and accurate localization using different US imaging platforms. An ultrasound image mid-plane detection accuracy of ±0.3 mm and a detectable tissue depth over 8.5 cm was achieved in the experiment. The system performance is tested under different configurations and system parameters. We also report the first experiment of arbitrary pattern injection to the B mode image and its application in accurate tool tracking.

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