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A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
by
Han, Fei
, He, Yanlin
, Zhou, Kangpeng
, Zhu, Hangwei
in
Cardiovascular disease
/ catheter shape sensing
/ Catheters
/ Equipment and supplies
/ Fiber optics
/ Magnetic resonance imaging
/ Mathematical optimization
/ Medical imaging
/ Methods
/ multi-core optical fiber
/ Neural networks
/ PSO-BP neural network
/ Radiation
/ Sensors
/ Surgeons
/ temperature compensation
/ Ultrasonic imaging
2023
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A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
by
Han, Fei
, He, Yanlin
, Zhou, Kangpeng
, Zhu, Hangwei
in
Cardiovascular disease
/ catheter shape sensing
/ Catheters
/ Equipment and supplies
/ Fiber optics
/ Magnetic resonance imaging
/ Mathematical optimization
/ Medical imaging
/ Methods
/ multi-core optical fiber
/ Neural networks
/ PSO-BP neural network
/ Radiation
/ Sensors
/ Surgeons
/ temperature compensation
/ Ultrasonic imaging
2023
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A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
by
Han, Fei
, He, Yanlin
, Zhou, Kangpeng
, Zhu, Hangwei
in
Cardiovascular disease
/ catheter shape sensing
/ Catheters
/ Equipment and supplies
/ Fiber optics
/ Magnetic resonance imaging
/ Mathematical optimization
/ Medical imaging
/ Methods
/ multi-core optical fiber
/ Neural networks
/ PSO-BP neural network
/ Radiation
/ Sensors
/ Surgeons
/ temperature compensation
/ Ultrasonic imaging
2023
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A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
Journal Article
A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
2023
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Overview
In this paper, we propose a novel shape-sensing method based on deep learning with a multi-core optical fiber for the accurate shape-sensing of catheters and guidewires. Firstly, we designed a catheter with embedded multi-core fiber containing three sensing outer cores and one temperature compensation middle core. Then, we analyzed the relationship between the central wavelength shift, the curvature of the multi-core Fiber Bragg Grating (FBG), and temperature compensation methods to establish a Particle Swarm Optimization (PSO) BP neural network-based catheter shape sensing method. Finally, experiments were conducted in both constant and variable temperature environments to validate the method. The average and maximum distance errors of the PSO-BP neural network were 0.57 and 1.33 mm, respectively, under constant temperature conditions, and 0.36 and 0.96 mm, respectively, under variable temperature conditions. This well-sensed catheter shape demonstrates the effectiveness of the shape-sensing method proposed in this paper and its potential applications in real surgical catheters and guidewire.
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