ArticleIEEE robotics and automation letters2018
Preoperative Needle Insertion Path Planning for Minimizing Deflection in Multilayered Tissues.
Article in IEEE robotics and automation letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Acoustic reflector-enabled forward-viewing ultrasound image-guided access.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- CRANE: A Redundant, Multi-Degree-of-Freedom Computed Tomography Robot for Heightened Needle Dexterity within a Medical Imaging Bore.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2024Article
- Needle Aligned Ultrasound Image-Guided Access Through Dual-Segment Array.IEEE transactions on bio-medical engineering · 2023Article
- Electrochemotherapy treatment safety under parallel needle deflection.Scientific reports · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
Fine needle deflection is a problem encountered during insertion into a soft tissue. Although an axial rotational insertion is an effective approach for minimizing this problem, needle deflection still depends on the insertion angle with respect to the tissue boundary. Since the human body consists of multi-layered tissues of various shapes and mechanical properties, preoperative planning of an optimal path is a key factor for achieving a successful insertion. In this paper, we propose an optimization-based preoperative path planning model that minimizes needle deflection during multi-layered tissue insertion. This model can determine the optimal path based on the sum of insertion angles with respect to each tissue boundary that the needle passes through. To increase the accuracy of the model, we incorporated the effect of distances from tissue boundaries and the probability that the deflection is acceptable by incorporating weighting factors into the model. To validate the model, we performed experiments involving four scenarios of two- and three-layered tissues. The results showed that the proposed model is capable of determining the optimal insertion path in all scenarios.
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