M E Karar1, D R Merk, C Chalopin, T Walther, V Falk, O Burgert. 1. Innovation Center Computer Assisted Surgery, Universität Leipzig, Semmelweisstrasse 14, 04103 Leipzig, Germany. mohamed.karar@medizin.uni-leipzig.de
Abstract
PURPOSE: Transapical aortic valve implantation (TA-AVI) is a new minimally invasive surgical treatment of aortic stenosis for high-risk patients. The placement of aortic valve prosthesis (AVP) is performed under 2D X-ray fluoroscopic guidance. Difficult clinical complications can arise if the implanted valve is misplaced. Therefore, we present a method to track the AVP in 2D X-ray fluoroscopic images in order to improve the accuracy of the TA-AVI. METHODS: The proposed tracking method includes the template matching approach to estimate the position of AVP and a shape model of the prosthesis to extract the corner points of the AVP in each image of sequence. To start the AVP tracking procedure, an initialization step is performed by manually defining the corner points of the prosthesis in the first image of sequence to provide the required algorithm parameters such as the AVP model parameters. RESULTS: We evaluated the AVP tracking method on six 2D intra-operative fluoroscopic image sequences. The results of automatic AVP localization agree well with manually defined AVP positions. The maximum localization errors of tracked prosthesis are less than 1 mm and within the clinical accepted range. CONCLUSIONS: For assisting the TA-AVI, a method for tracking the AVP in 2D X-ray fluoroscopic image sequences has been developed. Our AVP tracking method is a first step toward automatic optimal placement of the AVP during the TA-AVI.
PURPOSE: Transapical aortic valve implantation (TA-AVI) is a new minimally invasive surgical treatment of aortic stenosis for high-risk patients. The placement of aortic valve prosthesis (AVP) is performed under 2D X-ray fluoroscopic guidance. Difficult clinical complications can arise if the implanted valve is misplaced. Therefore, we present a method to track the AVP in 2D X-ray fluoroscopic images in order to improve the accuracy of the TA-AVI. METHODS: The proposed tracking method includes the template matching approach to estimate the position of AVP and a shape model of the prosthesis to extract the corner points of the AVP in each image of sequence. To start the AVP tracking procedure, an initialization step is performed by manually defining the corner points of the prosthesis in the first image of sequence to provide the required algorithm parameters such as the AVP model parameters. RESULTS: We evaluated the AVP tracking method on six 2D intra-operative fluoroscopic image sequences. The results of automatic AVP localization agree well with manually defined AVP positions. The maximum localization errors of tracked prosthesis are less than 1 mm and within the clinical accepted range. CONCLUSIONS: For assisting the TA-AVI, a method for tracking the AVP in 2D X-ray fluoroscopic image sequences has been developed. Our AVP tracking method is a first step toward automatic optimal placement of the AVP during the TA-AVI.
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