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Proceedings Paper

Automated identification of retained surgical items in radiological images
Author(s): Gady Agam; Lin Gan; Mario Moric; Vicko Gluncic
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Paper Abstract

Retained surgical items (RSIs) in patients is a major operating room (OR) patient safety concern. An RSI is any surgical tool, sponge, needle or other item inadvertently left in a patients body during the course of surgery. If left undetected, RSIs may lead to serious negative health consequences such as sepsis, internal bleeding, and even death. To help physicians efficiently and effectively detect RSIs, we are developing computer-aided detection (CADe) software for X-ray (XR) image analysis, utilizing large amounts of currently available image data to produce a clinically effective RSI detection system. Physician analysis of XRs for the purpose of RSI detection is a relatively lengthy process that may take up to 45 minutes to complete. It is also error prone due to the relatively low acuity of the human eye for RSIs in XR images. The system we are developing is based on computer vision and machine learning algorithms. We address the problem of low incidence by proposing synthesis algorithms. The CADe software we are developing may be integrated into a picture archiving and communication system (PACS), be implemented as a stand-alone software application, or be integrated into portable XR machine software through application programming interfaces. Preliminary experimental results on actual XR images demonstrate the effectiveness of the proposed approach.

Paper Details

Date Published: 17 March 2015
PDF: 7 pages
Proc. SPIE 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180X (17 March 2015); doi: 10.1117/12.2082384
Show Author Affiliations
Gady Agam, Rapid Medical Technologies (United States)
Lin Gan, Rapid Medical Technologies (United States)
Mario Moric, Rapid Medical Technologies (United States)
Vicko Gluncic, Rapid Medical Technologies (United States)


Published in SPIE Proceedings Vol. 9418:
Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations
Tessa S. Cook; Jianguo Zhang, Editor(s)

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