Paper
12 March 2014 Needle localization using a moving stylet/catheter in ultrasound-guided regional anesthesia: a feasibility study
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Abstract
Despite the wide range and long history of ultrasound guided needle insertions, an unresolved issue in many cases is clear needle visibility. A well-known ad hoc technique to detect the needle is to move the stylet and look for changes in the needle appearance. We present a new method to automatically locate a moving stylet/catheter within a stationary cannula using motion detection. We then use this information to detect the needle trajectory and the tip. The differences between the current frame and the previous frame are detected and localized, to minimize the influence of tissue global motions. A polynomial fit based on the detected needle axis determines the estimated stylet shaft trajectory, and the extent of the differences along the needle axis represents the tip. Over a few periodic movements of the stylet including its full insertion into the cannula to the tip, a combination of polynomial fits determines the needle trajectory and the last detected point represents the needle tip. Experiments are conducted in water bath and bovine muscle tissue for several stylet/catheter materials. Results show that a plastic stylet has the best needle shaft and tip localization accuracy in the water bath with RMSE = 0:16 mm and RMSE = 0:51 mm, respectively. In the bovine tissue, the needle tip was best localized with the plastic catheter with RMSE = 0:33 mm. The stylet tip localization was most accurate with the steel stylet, with RMSE = 2:81 mm and the shaft was best localized with the plastic catheter, with RMSE = 0:32 mm.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Parmida Beigi and Robert Rohling "Needle localization using a moving stylet/catheter in ultrasound-guided regional anesthesia: a feasibility study", Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 90362Q (12 March 2014); https://doi.org/10.1117/12.2043957
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Tissues

Visibility

Ultrasonography

Image segmentation

Motion detection

Transducers

Detection and tracking algorithms

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