A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber
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 compensati...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/16/7243 |
| _version_ | 1797583234271281152 |
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| author | Fei Han Yanlin He Hangwei Zhu Kangpeng Zhou |
| author_facet | Fei Han Yanlin He Hangwei Zhu Kangpeng Zhou |
| author_sort | Fei Han |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T23:35:59Z |
| format | Article |
| id | doaj.art-c8ab6c4f07574a54a933d8726b68aeb6 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T23:35:59Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c8ab6c4f07574a54a933d8726b68aeb62023-11-19T02:58:49ZengMDPI AGSensors1424-82202023-08-012316724310.3390/s23167243A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical FiberFei Han0Yanlin He1Hangwei Zhu2Kangpeng Zhou3Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing 100192, ChinaKey Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing 100192, ChinaKey Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing 100192, ChinaKey Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing 100192, ChinaIn 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.https://www.mdpi.com/1424-8220/23/16/7243multi-core optical fibercatheter shape sensingPSO-BP neural networktemperature compensation |
| spellingShingle | Fei Han Yanlin He Hangwei Zhu Kangpeng Zhou A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber Sensors multi-core optical fiber catheter shape sensing PSO-BP neural network temperature compensation |
| title | A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber |
| title_full | A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber |
| title_fullStr | A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber |
| title_full_unstemmed | A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber |
| title_short | A Novel Catheter Shape-Sensing Method Based on Deep Learning with a Multi-Core Optical Fiber |
| title_sort | novel catheter shape sensing method based on deep learning with a multi core optical fiber |
| topic | multi-core optical fiber catheter shape sensing PSO-BP neural network temperature compensation |
| url | https://www.mdpi.com/1424-8220/23/16/7243 |
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