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Automatic determination of optimal viewing angle for the coronary lesion observation in rotationnal X-ray angiography

Abstract : The thesis work deals with the planning of minimally invasive surgery of coronary artery lesions. The physician performs a coronarography following by a percutaneous transluminal angioplasty. The X-ray rotational angiography permits to visualize the lumen artery under different projection angles in several cardiac cycles. From these 2D projections, a 3D+T reconstruction of coronary arteries can be obtained. Our goal is to determine automatically from this 3D+T sequence, the optimal angiographic viewing angle of the stenotic segment. Several steps are proposed to compute the optimal angular position of the C-arm. Firstly, a mosaic-based tree matching algorithm of the 3D+T sequence is proposed to follow the stenotic lesion in the whole cardiac cycle. A pair-wise inexact tree matching is performed to build a tree union between successive trees. Next, these union trees are merged to obtain the mosaic tree which represents the most complete tree of the sequence. To take into account the non-rigid movement of coronary arteries during the cardiac cycle and their topology variations due to the 3D reconstruction or segmentation, similarity measures based on hierarchical and geometrical features are used. Artificial nodes are also inserted. With this global tree sequence matching, we propose secondly a new method to determine the optimal viewing angle of the stenotic lesion throughout the cardiac cycle. This 2D angiographic view which is proposed for three regions of interest (single segment, multiple segment or bifurcation) is computed from four criteria: the foreshortening, the external and internal overlap and the bifurcation opening angle rates. The optimal view shows the segment in its most extended and unobstructed dimension. This 2D view can be optimal either for the deployment of the stent or for the catheter guidance (from the root to the lesion). Our different algorithms are evaluated on real sequence (CT segmentation) and 41 simulated sequences.
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Submitted on : Friday, January 6, 2017 - 3:48:12 AM
Last modification on : Wednesday, September 14, 2022 - 10:20:04 AM
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  • HAL Id : tel-01427735, version 1


Hélène Feuillâtre. Automatic determination of optimal viewing angle for the coronary lesion observation in rotationnal X-ray angiography. Signal and Image processing. Université Rennes 1, 2016. English. ⟨NNT : 2016REN1S039⟩. ⟨tel-01427735⟩



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