ArticleIEEE sensors journal2022
Lie-Group Theoretic Approach to Shape-Sensing Using FBG-Sensorized Needles Including Double-Layer Tissue and S-Shape Insertions.
Article in IEEE sensors journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- A Framework to Optimize Channel and Active Area Usage in Multicore Fibers for Needle Shape Sensing.Journal of medical robotics research · 2026Article
- Evaluation of Fiber Optic Shape Sensing Models for Minimally Invasive Prostate Needle Procedures Using OFDR Data.IEEE sensors journal · 2025Article
- In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures.IEEE robotics and automation letters · 2024Article
- FBG-based Shape-Sensing to Enable Lateral Deflection Methods of Autonomous Needle Insertion.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2024Article
- Hybrid Deep Learning and Model-Based Needle Shape Prediction.IEEE sensors journal · 2024Article
- Fully Distributed Shape Sensing of a Flexible Surgical Needle Using Optical Frequency Domain Reflectometry for Prostate Interventions.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation · 2024Article
- Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.ArXiv · 2023Article
- Optical Fiber -Based Needle Shape Sensing: Three-channel Single Core vs. Multicore Approaches.... International Symposium on Medical Robotics. International Symposium on Medical Robotics · 2023Article
- Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.Journal of medical robotics researchArticle
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Flexible bevel-tipped needles are often used for needle insertion in minimally-invasive surgical techniques due to their ability to be steered in cluttered environments. Shapesensing enables physicians to determine the location of needles intra-operatively without requiring radiation of the patient, enabling accurate needle placement. In this paper, we validate a theoretical method for flexible needle shape-sensing that allows for complex curvatures, extending upon a previous sensor-based model. This model combines curvature measurements from fiber Bragg grating (FBG) sensors and the mechanics of an inextensible elastic rod to determine and predict the 3D needle shape during insertion. We evaluate the model's shape sensing capabilities in C- and S-shape insertions in single-layer isotropic tissue, and C-shape insertions in two-layer isotropic tissue. Experiments on a four-active area, FBG-sensorized needle were performed in varying tissue stiffnesses and insertion scenarios under stereo vision to provide the 3D ground truth needle shape. The results validate a viable 3D needle shape-sensing model accounting for complex curvatures in flexible needles with mean needle shape sensing root-mean-square errors of 0.160 ± 0.055 mm over 650 needle insertions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.