TY - JOUR
T1 - Needle Segmentation Using GAN
T2 - Restoring Thin Instrument Visibility in Robotic Ultrasound
AU - Jiang, Zhongliang
AU - Li, Xuesong
AU - Chu, Xiangyu
AU - Karlas, Angelos
AU - Bi, Yuan
AU - Cheng, Yingsheng
AU - Au, K. W.Samuel
AU - Navab, Nassir
N1 - Publisher Copyright:
© 1963-2012 IEEE
PY - 2024
Y1 - 2024
N2 - Ultrasound-guided percutaneous needle insertion is a standard procedure employed in both biopsy and ablation in clinical practices. However, due to the complex interaction between tissue and instrument, the needle may deviate from the in-plane view, resulting in a lack of close monitoring of the percutaneous needle. To address this challenge, we introduce a robot-assisted ultrasound (US) imaging system designed to seamlessly monitor the insertion process and autonomously restore the visibility of the inserted instrument when misalignment happens. To this end, the adversarial structure is presented to encourage the generation of segmentation masks that align consistently with the ground truth in high-order space. This study also systematically investigates the effects on segmentation performance by exploring various training loss functions and their combinations. When misalignment between the probe and the percutaneous needle is detected, the robot is triggered to perform transverse searching to optimize the positional and rotational adjustment to restore needle visibility. The experimental results on ex-vivo porcine samples demonstrate that the proposed method can precisely segment the percutaneous needle (with a tip error of 0.37±0.29mm and an angle error of 1.19±0.29◦). Furthermore, the needle appearance can be successfully restored under the repositioned probe pose in all 45 trials, with repositioning errors of 1.51 ± 0.95mm and 1.25 ± 0.79◦,.
AB - Ultrasound-guided percutaneous needle insertion is a standard procedure employed in both biopsy and ablation in clinical practices. However, due to the complex interaction between tissue and instrument, the needle may deviate from the in-plane view, resulting in a lack of close monitoring of the percutaneous needle. To address this challenge, we introduce a robot-assisted ultrasound (US) imaging system designed to seamlessly monitor the insertion process and autonomously restore the visibility of the inserted instrument when misalignment happens. To this end, the adversarial structure is presented to encourage the generation of segmentation masks that align consistently with the ground truth in high-order space. This study also systematically investigates the effects on segmentation performance by exploring various training loss functions and their combinations. When misalignment between the probe and the percutaneous needle is detected, the robot is triggered to perform transverse searching to optimize the positional and rotational adjustment to restore needle visibility. The experimental results on ex-vivo porcine samples demonstrate that the proposed method can precisely segment the percutaneous needle (with a tip error of 0.37±0.29mm and an angle error of 1.19±0.29◦). Furthermore, the needle appearance can be successfully restored under the repositioned probe pose in all 45 trials, with repositioning errors of 1.51 ± 0.95mm and 1.25 ± 0.79◦,.
KW - Medical robotics
KW - Needle Segmentation
KW - Robotic ultrasound
KW - Ultrasound segmentation
UR - http://www.scopus.com/inward/record.url?scp=85208408711&partnerID=8YFLogxK
U2 - 10.1109/TIM.2024.3451569
DO - 10.1109/TIM.2024.3451569
M3 - Article
AN - SCOPUS:85208408711
SN - 0018-9456
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
ER -