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 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 < 0.01 compared with conventional MSER methods, 93.7% average detection accuracy, and 21 fps average speed. [ABSTRACT FROM AUTHOR]