Paper
21 March 2016 Guidewire path tracking and segmentation in 2D fluoroscopic time series using device paths from previous frames
Martin G. Wagner, Charles M. Strother, Charles A. Mistretta
Author Affiliations +
Abstract
Recent efforts to perform a 3D reconstruction of interventional devices such as guidewires from monoplane and biplane fluoroscopic images require the segmentation of the exact device path in the respective 2D projection images. The segmentation of the device in low dose fluoroscopy images can be challenging since noise and motion artifacts degrade the image quality. Additionally, extracting the device path from the segmented region may result in ambiguous results due to overlapping device parts or discontinuities in the device segmentation. The purpose of this work is to present a novel guidewire tracking and segmentation algorithm, which segments the device region based on three different features based on a ridge detection filter, noise reduction for curvilinear structures as well as an a priori probability map. The features are calculated from background subtracted as well as unsubtracted fluoroscopic images. The device path extraction is based on a topology preserving thinning algorithm followed by a path search, which minimizes a cost function based on distance and directional difference between adjacent segments as well as the similarity to the device path extracted from the previous frame. The quantitative evaluation was performed using 7 data sets acquired from a canine study. Device shapes with different complexities are compared to semi-automatic segmentations. An average segmentation accuracy of 0.50 0.41 mm was achieved where each point along the device was compared to the point on the reference device centerline with the same distance to the device tip. In all cases the device path could be resolved correctly, which would allow a more accurate and reliable reconstruction of the 3D path of the device.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Martin G. Wagner, Charles M. Strother, and Charles A. Mistretta "Guidewire path tracking and segmentation in 2D fluoroscopic time series using device paths from previous frames", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97842B (21 March 2016); https://doi.org/10.1117/12.2216540
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Image segmentation

Detection and tracking algorithms

Image processing algorithms and systems

3D modeling

Denoising

Reconstruction algorithms

Feature extraction

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