Ultrasound guided automatic localization of needle insertion site for epidural anesthesia

• Published in: 2013 IEEE International Conference on Mechatronics and Automation pp. 985 - 990
• Main Authors: Shuang Yu, Kok Kiong Tan, Chengyao Shen, Sia, Alex Tiong Heng
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2013
• Subjects: Anesthesia; Automatic Identification; Epidural Anesthesia; Imaging; Local Normalization; Needles; Noise; Probes; Speckle; Template Matching; Ultrasonic imaging; Ultrasound Imaging Guidance
• ISBN: 1467355577; 9781467355575
• ISSN: 2152-7431; 2152-744X
• DOI: 10.1109/ICMA.2013.6618049

In this paper, ultrasound imaging is utilized to detect the anatomical structure of the lumbar spine based on which an image processing algorithm will search for key features to identify the optimal needle insertion site. The key challenge lies in the nature of ultrasound images which are obscure and have low spatial resolution, induced by contamination from random speckle noises. In order to improve the interpretability of ultrasound images, a modified version of local normalization using the Difference of Gaussian algorithm is first used for pre-processing to filter the speckle noise and extract the main anatomical structure in the raw images obtained. Meanwhile, local means induced by non-uniform wave reflection rate is also successfully removed by the proposed pre-processing algorithm, thus a potential element that may degrade the image recognition accuracy is excluded. In the second stage, a template matching algorithm, augmented with a position correlation function, automatically identifies the key features of interest and thus the insertion site. The approach has been tested on more than 200 ultrasound images with a 100% success rate. The proposed system allows the anesthetist to use the approach efficiently without the burden of interpreting real time ultrasound images.