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Automatic detection of hemorrhage and surgical instrument in laparoscopic surgery image

Authors: Kyungmin Jo; Bareum Choi; Songe Choi; Youngjin Moon; Jaesoon Choi;

Automatic detection of hemorrhage and surgical instrument in laparoscopic surgery image

Abstract

In this paper, we propose a new method for detecting hemorrhage areas and surgical instruments in robot-assisted laparoscopic surgery images. The proposed scheme utilizes CIELAB information to identify a region of interest (ROI) and segment it. Histogram equalization and Otsu's method are also adopted to compute the detection threshold. Detection is performed automatically and additional adjustment of parameters is not needed. Experiments to verify the proposed algorithm were conducted using actual robot-assisted laparoscopic surgery images. Using the proposed algorithm, the average time consumption was 0.37 s per frame for hemorrhage identification and 0.11 s for instrument detection. The sensitivities were also high enough for practical application.

Related Organizations
Keywords

Humans, Laparoscopy, Surgical Instruments, Algorithms

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Average
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