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Proceedings Paper

Extended contrast detection on fluoroscopy and angiography for image-guided trans-catheter aortic valve implantations (TAVI)
Author(s): Yinxiao Liu; Rui Liao; Xudong Lv
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Paper Abstract

Navigation and deployment of the prosthetic valve during trans-catheter aortic valve implantation (TAVI) can be greatly facilitated with 3-D models showing detailed anatomical structures. Fast and robust automatic contrast detection at the aortic root on X-ray images is indispensable for automatically triggering a 2-D/3-D registration to align the 3-D model. Previously, we have proposed an automatic method for contrast detection at the aortic root on fluoroscopic and angiographic sequences [4]. In this paper, we extend that algorithm in several ways, making it more robust to handle more general and difficult cases. Specifically, the histogram likelihood ratio test is multiplied with the histogram portion computation to handle faint contrast cases. Histogram mapping corrects sudden changes in the global brightness, thus avoiding potential false positives. Respiration and heart beating check further reduces the false positive rate. In addition, a probe mask is introduced to enhance the contrast feature curve when the dark ultrasound probe partially occludes the aortic root. Lastly, a semi-global registration method for aligning the aorta shape model is implemented to improve the robustness of the algorithm with respect to the selection of region of interest (ROI) containing the aorta. The extended algorithm was evaluated on 100 sequences, and improved the detection accuracy from 94% to 100%, compared to the original method. Also, the robustness of the extended algorithm was tested with 20 different shifts of the ROI, and the error rate was as low as 0.2%, in comparison to 6.6% for the original method.

Paper Details

Date Published: 17 February 2012
PDF: 9 pages
Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 831618 (17 February 2012); doi: 10.1117/12.911741
Show Author Affiliations
Yinxiao Liu, Siemens Corporate Research (United States)
Rui Liao, Siemens Corporate Research (United States)
Xudong Lv, Siemens Corporate Research (United States)


Published in SPIE Proceedings Vol. 8316:
Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Kenneth H. Wong, Editor(s)

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