TY - GEN
T1 - Needle Insertion Path Planning System for Lower Abdominal Insertion Based on CT Images
AU - Matsumoto, Ryutaro
AU - Tsumura, Ryosuke
AU - Iwata, Hiroyasu
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - For percutaneous needle insertion in the lower abdomen, preoperative insertion path planning with CT imaging is important. Previous studies have shown that needle deflection can be minimized by selecting an insertion path for which the sum of the insertion angles on the tissue boundaries is minimized. To apply the concept of path planning to the clinical setting, a system must be developed to automatically calculate the insertion angle and determine the optimal insertion path on CT images. We herein present a method for multilayered tissue boundary detection in the lower abdomen and insertion angle calculation along the insertion path based on the boundary detection. Because this detection method does not depend on the tissue shape, the boundary points showing a peak brightness change on each insertion path are detected and connected. The experimental results showed an average insertion angle error in the skin, muscle, and bowel of 0.68, 0.99, and 5.3 degrees, respectively.
AB - For percutaneous needle insertion in the lower abdomen, preoperative insertion path planning with CT imaging is important. Previous studies have shown that needle deflection can be minimized by selecting an insertion path for which the sum of the insertion angles on the tissue boundaries is minimized. To apply the concept of path planning to the clinical setting, a system must be developed to automatically calculate the insertion angle and determine the optimal insertion path on CT images. We herein present a method for multilayered tissue boundary detection in the lower abdomen and insertion angle calculation along the insertion path based on the boundary detection. Because this detection method does not depend on the tissue shape, the boundary points showing a peak brightness change on each insertion path are detected and connected. The experimental results showed an average insertion angle error in the skin, muscle, and bowel of 0.68, 0.99, and 5.3 degrees, respectively.
UR - http://www.scopus.com/inward/record.url?scp=85064133582&partnerID=8YFLogxK
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U2 - 10.1109/ROBIO.2018.8664883
DO - 10.1109/ROBIO.2018.8664883
M3 - Conference contribution
AN - SCOPUS:85064133582
T3 - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
SP - 182
EP - 185
BT - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
Y2 - 12 December 2018 through 15 December 2018
ER -