Skip to main content

Ultrasound Images For Accurate Epidural Needle Insertion.

Vaughan, N. and Dubey, V. N., 2017. Ultrasound Images For Accurate Epidural Needle Insertion. In: Design of Medical Devices 2017, 9-13 April 2017, Minneapolis, MN, USA.

Full text available as:

DMD2017-3494.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


Official URL:


This work presents development and testing of image processing algorithms for the automatic detection of landmarks within ultrasound images. The aim was to automate ultrasound analysis, for use during the process of epidural needle insertion. For epidural insertion, ultrasound is increasingly used to guide the needle into the epidural space. Ultrasound can improve the safety of epidural and was recommended by the 2008 NICE guidelines (National Institute for Health and Care Excellence). Without using ultrasound, there is no way for the anaesthetist to observe the location of the needle within the ligaments requiring the use of their personal judgment which may lead to injury. If the needle stops short of the epidural space, the anaesthetic is ineffective. If the needle proceeds too deep, it can cause injuries ranging from headache, to permanent nerve damage or death. Ultrasound of the spine is particularly difficult, because the complex bony structures surrounding the spine limit the ultrasound beam acoustic windows. Additionally, the important structures for epidural that need to be observed are located deeper than other conventional procedures such as peripheral nerve block. This is why a low frequency, curved probe (2-5 MHz) is used, which penetrates deeper but decreases in resolution. The benefits of automating ultrasound are to enable real-time ultrasound analysis on the live video, mitigate human error, and ensure repeatability by avoiding variation in perception by different users.

Item Type:Conference or Workshop Item (Paper)
Group:Faculty of Science & Technology
ID Code:28212
Deposited By: Symplectic RT2
Deposited On:27 Mar 2017 15:50
Last Modified:14 Mar 2022 14:03


Downloads per month over past year

More statistics for this item...
Repository Staff Only -