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Sensing Technologies for Guidance During Needle-Based Interventions

delete2024-01-01
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PRE
AI
Z
Zhuoqi Cheng *
M
Maria Koskinopoulou
S
Sophia Bano
D
Danail Stoyanov
T
Thiusius Rajeeth Savarimuthu
L
Leonardo S. Mattos
DOI:10.1109/TIM.2024.3441017delete
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摘要

摘要

En 中文
Needle intervention is widely employed in clinical practices, such as biopsies, regional anesthesia, blood sampling, neurosurgery, and brachytherapy. Traditional needle insertion relies on surgeon expertise and kinesthetic feedback, yet accurately targeting deep tissue structures remains challenging. To address this, significant research has advanced sensing technologies to aid insertion accuracy. This article comprehensively reviews recent developments in needle insertion sensing techniques, encompassing needle tip position tracking, proximity measurement, and puncture detection. It evaluates these methods across metrics, including accuracy, cost-effectiveness, portability, compatibility, noise resistance capability, technology readiness level (TRL), and future trends. Emerging research directions highlight advancements in machine learning integration, miniaturization, and enhanced multimodal sensing capabilities to improve procedural outcomes and expand application domains.
Keyword:
Needles
Robot sensing systems
Sensors
Accuracy
Optical imaging
Optical fibers
Real-time systems
Biomedical sensor
image-guided insertion
needle tip tracking
proximity sensing
puncture detection

期刊

IEEE Transactions on Instrumentation and Measurement 封面图
IEEE Transactions on Instrumentation and Measurement
IF:
5.9
论文数:
2.0W
被引数:
5.8W

机构

H
Heriot Watt University
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6.0K
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被引数: 57
U
University of Southern Denmark
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2.1W
论文数: 2.0W
被引数: 2.9W
E
engineering & physical sciences research council (epsrc)
学者数:
709
论文数: 470
被引数: 1
U
uk research & innovation (ukri)
学者数:
2.7W
论文数: 2.3W
被引数: 32
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