Applying maximally stable extremal regions and local binary patterns for guide-wire detecting in percutaneous coronary intervention

Intervention surgery strongly requires information on the guide-wire position under the monitoring of X-ray video. Hence, the related researches such as guide-wire detecting or tracking have become widespread. However, most of the existing methods require a lot of resources for computing or large da...

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Bibliographic Details
Published in:IET image processing 2019-11, Vol.13 (13), p.2579-2586
Main Authors: Pusit, Prasong, Xie, Xiao-Liang, Hou, Zeng-Guang
Format: Article
Language:English
Subjects:
anatomical skeleton contours
blood vessels
conventional MSER methods
guide‐wire position
guide‐wire recognition
guide‐wire tip detection
image filtering
image sequences
local binary patterns
maximally stable extremal regions
medical image processing
modified multifilters
object detection
object tracking
percutaneous coronary intervention surgery
region area range filter
region detection
Research Article
stroke width variation filter
surgery
training data
training templates
video signal processing
X‐ray imaging
X‐ray video monitoring
X‐ray video sequence
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Summary:Intervention surgery strongly requires information on the guide-wire position under the monitoring of X-ray video. Hence, the related researches such as guide-wire detecting or tracking have become widespread. However, most of the existing methods require a lot of resources for computing or large data for training since the X-ray videos have internal physicals such as anatomical skeleton contours and organs that are quite similar to a guide-wire. This work presents a practical method that only requires a moderate number of training data for detecting a guide-wire tip in an X-ray video sequence during the percutaneous coronary intervention surgery. The method applies maximally stable extremal regions (MSER) combine with modified multi-filters (region area range filter and stroke width variation filter) for region detection and local binary patterns (LBP) for guide-wire recognition. The motivation for applying MSER and LBP are the robust efficacy and the low requirement of resources. The approach evaluated 20 different sequences of X-ray videos, a total of 1295 frames. 50 selected frames were used as training templates and others to experiment. The method was successfully performed to the detecting guide-wires with p-value 
ISSN:1751-9659
1751-9667
DOI:10.1049/iet-ipr.2018.6652