The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia

Meng-Chun Kao; Chien-Kun Ting; Wen-Chuan Kuo

doi:10.1117/12.2289750

12 February 2018 The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia

Meng-Chun Kao, Chien-Kun Ting, Wen-Chuan Kuo

Author Affiliations +

Proceedings Volume 10484, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVI; 104840D (2018) https://doi.org/10.1117/12.2289750
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

Incorrect placement of the needle causes medical complications in the epidural block, such as dural puncture or spinal cord injury. This study proposes a system which combines an optical coherence tomography (OCT) imaging probe with an automatic identification (AI) system to objectively identify the position of the epidural needle tip. The automatic identification system uses three features as image parameters to distinguish the different tissue by three classifiers. Finally, we found that the support vector machine (SVM) classifier has highest accuracy, specificity, and sensitivity, which reached to 95%, 98%, and 92%, respectively.

Conference Presentation

Citation Download Citation

Meng-Chun Kao, Chien-Kun Ting, and Wen-Chuan Kuo "The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia", Proc. SPIE 10484, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVI, 104840D (12 February 2018); https://doi.org/10.1117/12.2289750

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE