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An Automatic 3-D Reconstruction of Coronary Arteries by Stereopsis

  • Patient Facing Systems
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Abstract

Stereopsis of X-ray images can produce 3D tree of coronary arteries up to a certain accuracy level with a lower dose of radiation when compared to computer tomography (CT). In this study, a novel and complete automatic system is designed that covers preprocessing, segmentation, matching and reconstruction steps for that purpose. First, an automatic and novel pattern recognition technique is applied for extraction of the bifurcation points with their diameters recorded in a map. Then, a novel optimization algorithm is run for matching the branches efficiently which is based on that map and the epipolar geometry of stereopsis. Finally, cut branches are fixed one by one at the bifurcations for completing the 3D reconstruction. This method prevails the similar ones in the literature with this novelty since it automatically and inherently prevents the wrong overlapping of branches. Other essential problems like correct detection of the bifurcations and accurate calibration parameters and fast overlapping of matched branches are addressed at acceptable levels. The accuracy of bifurcation extraction is high at 90 % with 96 % sensitivity. Accuracy of vessel centerlines has rootmean-square (rms) error smaller than 0.57 mm for 20 different patients. For phantom model, rms error is 0.75 ± 0.8 mm in 3D localization.

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Acknowledgments

We specially thank to Prof. Omer Etlik and Prof Kamran Mahmutyazıcıoğlu(Fatih University, Sema Application and Research Hospital, Istanbul, Turkey) and Dr. Fatih Beşiroğlu (Marmara University, Pendik Application and Research Hospital, Istanbul, Turkey) for their contributions.

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  1. Yalova University, Yalova, Turkey

    Mufit Cetin & Ali Iskurt

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  1. Mufit Cetin
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  2. Ali Iskurt
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Correspondence to Mufit Cetin.

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The authors declare that they have no conflict of interest.

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This article is part of the Topical Collection on Patient Facing Systems

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Cetin, M., Iskurt, A. An Automatic 3-D Reconstruction of Coronary Arteries by Stereopsis. J Med Syst 40, 94 (2016). https://doi.org/10.1007/s10916-016-0455-z

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