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Published on: June 3, 2018
Robust catheter identification and tracking in X-ray angiographic sequences
Insights
This study presents an automatic method to detect and track catheters in X-ray angiography images, improving diagnostic accuracy for coronary artery disease (CAD). The novel approach enhances image quality and precisely identifies the catheter, crucial for reliable vessel extraction in CAD diagnosis.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Cardiovascular Diagnostics
Background:
- Coronary artery disease (CAD) is a leading global cause of mortality.
- X-ray angiography is the standard diagnostic tool for CAD, but image quality issues often hinder analysis.
- Catheter presence in angiography images complicates accurate vessel extraction due to structural similarities.
Purpose of the Study:
- To develop a fully automatic method for catheter detection and tracking in X-ray angiography sequences.
- To address image quality degradation issues affecting CAD diagnosis.
- To improve the reliability of vessel extraction in the presence of catheters.
Main Methods:
- Utilizing a vesselness map and guided filter for image smoothing.
- Employing Hough transform for initial catheter detection in the first frame.
- Fitting a second-order polynomial for accurate catheter tracking throughout the sequence.
Main Results:
- The proposed method successfully detects and tracks catheters in X-ray angiography sequences.
- Achieved a precision of 0.9597 on 25 tested sequences.
- Demonstrated robustness in handling image quality degradations.
Conclusions:
- The developed automatic catheter detection and tracking method is effective for X-ray angiography.
- This technique can significantly aid in improving the accuracy of vessel extraction for CAD diagnosis.
- The method offers a valuable tool for enhancing the clinical utility of cardiovascular imaging.
Abstract:
Coronary artery disease (CAD) is one of the major causes of death worldwide. Today X-ray angiography is a standard method for CAD diagnosis. Usually, the quality of these images is not good enough. Noise, camera and heart motions, non-uniform illumination and even the presence of catheter are sources of quality degradation. The existence of catheter can produce difficulties in vessel extraction methods because catheter is structurally similar to arteries. In this paper we propose a fully automatic method for catheter detection and tracking during the whole angiography sequence. In this method with a vesselness map, we smooth each frame using guided filter. The catheter is detected in the first frame using Hough transform. We then fit a second order polynomial on the catheter and accurately track it throughout the sequence. Our method is tested on 25 X-ray angiography sequences where a precision of 0.9597 is achieved.
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