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Augmenting CT cardiac roadmaps with segmented streaming ultrasound

Qi Duan; Guy Shechter; Luis F. Gutiérrez; Douglas Stanton; Lyubomir Zagorchev; Andrew F. Laine; Daniel R. Elgort

Title:
Augmenting CT cardiac roadmaps with segmented streaming ultrasound
Author(s):
Duan, Qi
Shechter, Guy
Gutiérrez, Luis F.
Stanton, Douglas
Zagorchev, Lyubomir
Laine, Andrew F.
Elgort, Daniel R.
Date:
Type:
Articles
Department:
Biomedical Engineering
Permanent URL:
Book/Journal Title:
Medical imaging 2007 : Visualization and image-guided procedures : 18-20 February, 2007, San Diego, California, USA ; Proceedings of SPIE, vol. 6509
Publisher:
SPIE
Abstract:
Static X-ray computed tomography (CT) volumes are often used as anatomic roadmaps during catheter-based cardiac interventions performed under X-ray fluoroscopy guidance. These CT volumes provide a high-resolution depiction of soft-tissue structures, but at only a single point within the cardiac and respiratory cycles. Augmenting these static CT roadmaps with segmented myocardial borders extracted from live ultrasound (US) provides intra-operative access to real-time dynamic information about the cardiac anatomy. In this work, using a customized segmentation method based on a 3D active mesh, endocardial borders of the left ventricle were extracted from US image streams (4D data sets) at a frame rate of approximately 5 frames per second. The coordinate systems for CT and US modalities were registered using rigid body registration based on manually selected landmarks, and the segmented endocardial surfaces were overlaid onto the CT volume. The root-mean squared fiducial registration error was 3.80 mm. The accuracy of the segmentation was quantitatively evaluated in phantom and human volunteer studies via comparison with manual tracings on 9 randomly selected frames using a finite-element model (the US image resolutions of the phantom and volunteer data were 1.3 x 1.1 x 1.3 mm and 0.70 x 0.82 x 0.77 mm, respectively). This comparison yielded 3.70±2.5 mm (approximately 3 pixels) root-mean squared error (RMSE) in a phantom study and 2.58±1.58 mm (approximately 3 pixels) RMSE in a clinical study. The combination of static anatomical roadmap volumes and dynamic intra-operative anatomic information will enable better guidance and feedback for image-guided minimally invasive cardiac interventions.
Subject(s):
Biomedical engineering
Publisher DOI:
10.1117/12.711431
Item views:
138
Metadata:
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