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A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber.

Fei Han1,2, Yanlin He1,2, Hangwei Zhu1,2,3

  • 1Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing 100192, China.

Sensors (Basel, Switzerland)
|August 26, 2023
PubMed
Summary

This study introduces a deep learning shape-sensing method using multi-core optical fiber for precise catheter and guidewire shape detection. The novel approach achieves high accuracy in both constant and variable temperature environments.

Keywords:
PSO-BP neural networkcatheter shape sensingmulti-core optical fibertemperature compensation

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Area of Science:

  • Biomedical Engineering
  • Optical Fiber Sensing
  • Deep Learning Applications

Background:

  • Accurate shape sensing is critical for minimally invasive surgical tools like catheters and guidewires.
  • Existing methods face challenges with precision and temperature variations.
  • Multi-core optical fibers offer a promising platform for enhanced sensing capabilities.

Purpose of the Study:

  • To develop and validate a novel deep learning-based shape-sensing method for catheters and guidewires.
  • To leverage multi-core optical fiber technology for improved shape reconstruction accuracy.
  • To address the impact of temperature fluctuations on shape-sensing performance.

Main Methods:

  • Design of a catheter incorporating a multi-core optical fiber with sensing and temperature compensation cores.
  • Analysis of the relationship between central wavelength shift, multi-core Fiber Bragg Grating (FBG) curvature, and temperature.
  • Development of a Particle Swarm Optimization (PSO) optimized Backpropagation (BP) neural network for shape sensing.

Main Results:

  • Experimental validation in constant and variable temperature conditions demonstrated the method's effectiveness.
  • Achieved average distance errors of 0.57 mm (constant temp) and 0.36 mm (variable temp).
  • Maximum distance errors were recorded at 1.33 mm (constant temp) and 0.96 mm (variable temp).

Conclusions:

  • The proposed deep learning and multi-core optical fiber method enables accurate catheter and guidewire shape sensing.
  • The system demonstrates robust performance across varying temperatures.
  • This technology holds significant potential for enhancing real-world surgical applications.