Integrating robot‐assisted ultrasound tracking and 3D needle shape prediction for real‐time tracking of the needle tip in needle steering procedures

Abstract

Background Needle insertions have been used in several minimally invasive procedures for diagnostic and therapeutic purposes. Real‐time position of the needle tip is an important information in needle steering systems. Methods This work introduces a robot‐assisted ultrasound tracking (R‐AUST) system integrated with a needle shape prediction method to provide 3D position of the needle tip. The tracking system is evaluated in phantom and ex vivo beef liver tissues. Results An average error of 0.60 mm was found for needle insertion tests inside the phantom tissue. The R‐AUST integrated with shape prediction in the beef liver tissue was able to track the needle tip with an average and maximum error of 0.37 and 0.67 mm, respectively. The average error reported in this work is within the mean allowable needle placement error (<2.7 mm) in targeted procedures. Conclusions Integration of R‐AUST tracking method with needle shape prediction results in a reasonably accurate real‐time tracking suitable for ultrasound‐guided needle insertions.

Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization

“…In the medical domain, vision-based and marker-less surgical tool detection and tracking methods were reviewed in [ 80 , 81 , 82 ]. Other object tracking methods based on intraoperative imaging modalities include fluoroscopy-based [ 83 , 84 ], ultrasonography-based [ 85 , 86 ], and hybrid multimodalities [ 87 , 88 ], which combine ultrasound and endoscopic vision-based tracking as shown in Figure 3 . In [ 88 ], the more accurate ultrasound-based localization is used for less frequent initialization and reinitialization while endoscopic camera-based tracking is used for more timely motion tracking.…”

Kinematics modelling and dynamics analysis of an SMA-actuated active flexible needle for feedback-controlled manipulation in phantom

“…Characterizing the mechanical response of the needle is a preliminary step towards development of the models predicting the position of the needle during the insertion for active steering control and accurate placement of the needle. Vision-based measurement (VBM) [25], [26] is a rapidly rising approach to quantitatively characterize response of a system in a variety of modelling and control applications. Vision-based characterization of the needle's response is demonstrated to accomplish efficient control algorithms [27].…”