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Proceedings Paper

The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia
Author(s): Meng-Chun Kao; Chien-Kun Ting; Wen-Chuan Kuo
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Paper 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.

Paper Details

Date Published: 12 February 2018
PDF: 7 pages
Proc. SPIE 10484, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVI, 104840D (12 February 2018); doi: 10.1117/12.2289750
Show Author Affiliations
Meng-Chun Kao, National Yang-Ming Univ. (Taiwan)
Chien-Kun Ting, Taipei Veterans General Hospital, National Yang-Ming Univ. (Taiwan)
Wen-Chuan Kuo, National Yang-Ming Univ. (Taiwan)


Published in SPIE Proceedings Vol. 10484:
Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVI
Tuan Vo-Dinh; Anita Mahadevan-Jansen; Warren S. Grundfest M.D., Editor(s)

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