Abstract
Fine needles can easily be deflected, making accurate needle insertion into a tumor difficult. In particular, it is difficult to insert the needle into a tumor in the lower abdomen because the needle has to pass through various tissues. Therefore, for lower abdominal needle insertion, we intend to develop a planning method for the optimal insertion path to minimize the deflection based on computed tomography images. In this letter, we analyze the deflection while performing needle insertion with axial rotation under conditions of various insertion angles into individual tissues composing the lower abdomen (pork loin and porcine small bowel) and develop a basic planning procedure to determine the optimal insertion path based on the analysis. From the results, we confirmed that the insertion angle should be minimized as much as possible. We then develop a planning method based on insertion angles into individual tissues the needle needs to pass through. We assumed that it is possible to determine the optimal insertion path by providing a weighting factor to the effect of the insertion angle depending on the depth of insertion, considering that the effect of the insertion angle on deflection in deep places of the body is smaller than the effect around the body surface. To verify the concept of the proposed planning procedure, we perform experiments with a simple model composed of two tissues. From the results, we show that the optimal insertion path can be planned by setting the optimal ratio of individual weighting factors.
Original language | English |
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Article number | 7857784 |
Pages (from-to) | 1226-1231 |
Number of pages | 6 |
Journal | IEEE Robotics and Automation Letters |
Volume | 2 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2017 Apr |
Keywords
- Needle insertion
- Path planning
ASJC Scopus subject areas
- Control and Systems Engineering
- Biomedical Engineering
- Human-Computer Interaction
- Mechanical Engineering
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Control and Optimization
- Artificial Intelligence