ArticleProceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems2022
Toward FBG-Sensorized Needle Shape Prediction in Tissue Insertions.
Article in Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures.IEEE robotics and automation letters · 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
- Data-driven adaptive needle insertion assist for transperineal prostate interventions.Physics in medicine and biology · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Complex needle shape prediction remains an issue for planning of surgical interventions of flexible needles. In this paper, we validate a theoretical method for flexible needle shape prediction allowing for non-uniform curvatures, extending upon a previous sensor-based model which 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 effectiveness in single-layer isotropic tissue for shape sensing and shape prediction capabilities. Experiments on a four-active area, FBG-sensorized needle were performed in varying single-layer isotropic tissues under stereo vision to provide 3D ground truth of the needle shape. The results validate a viable 3D needle shape prediction model accounting for non-uniform curvatures in flexible needles with mean needle shape sensing and prediction root-mean-square errors of 0.479 mm and 0.892 mm, respectively.
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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.