Literature DB >> 19713148

Automatic generation of 3D coronary artery centerlines using rotational X-ray angiography.

Uwe Jandt1, Dirk Schäfer, Michael Grass, Volker Rasche.   

Abstract

A fully automated 3D centerline modeling algorithm for coronary arteries is presented. It utilizes a subset of standard rotational X-ray angiography projections that correspond to one single cardiac phase. The algorithm is based on a fast marching approach, which selects voxels in 3D space that belong to the vascular structure and introduces a hierarchical order. The local 3D propagation speed is determined by a combination of corresponding 2D projections filtered with a vessel enhancing kernel. The best achievable accuracy of the algorithm is evaluated on simulated projections of a virtual heart phantom, showing that it is capable of extracting coronary centerlines with an accuracy that is mainly limited by projection and volume quantization (0.25 mm). The algorithm is reasonably insensitive to residual motion, which means that it is able to cope with inconsistencies within the projection data set caused by limited gating accuracy and respiration. Its accuracy on clinical data is evaluated based on expert ratings of extracted models of 17 consecutive clinical cases (10 LCA, 7 RCA). A success rate of 93.5% (i.e. with no or slight deviations) is achieved compared to 58.8% success rate of semi-automatically extracted models.

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Year:  2009        PMID: 19713148     DOI: 10.1016/j.media.2009.07.010

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  7 in total

1.  Automated quantification of carotid artery stenosis on contrast-enhanced MRA data using a deformable vascular tube model.

Authors:  Avan Suinesiaputra; Patrick J H de Koning; Elena Zudilova-Seinstra; Johan H C Reiber; Rob J van der Geest
Journal:  Int J Cardiovasc Imaging       Date:  2011-12-09       Impact factor: 2.357

2.  A model-based reconstruction method for 3-D rotational coronary angiography.

Authors:  Lizhe Xie; Yining Hu; Jean-Claude Nunes; Jean-Jacques Bellanger; Marc Bedossa; Limin Luo; Christine Toumoulin
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

3.  Calibration-free device sizing using an inverse geometry x-ray system.

Authors:  Michael T Tomkowiak; Michael A Speidel; Amish N Raval; Michael S Van Lysel
Journal:  Med Phys       Date:  2011-01       Impact factor: 4.071

4.  Automatic image processing pipeline for tracking longitudinal vessel changes in magnetic resonance angiography.

Authors:  Chih-Yang Hsu; Yimei Li; Yuanyuan Han; Lucas Elijovich; Noah D Sabin; Tarek Abuelem; Radmehr Torabi; Austin Faught; Chia-Ho Hua; Paul Klimo; Thomas E Merchant; John T Lucas
Journal:  J Magn Reson Imaging       Date:  2019-03-07       Impact factor: 4.813

5.  Diameter Estimation of Fallopian Tubes Using Visual Sensing.

Authors:  Amir M Hajiyavand; Matthew J Graham; Karl D Dearn
Journal:  Biosensors (Basel)       Date:  2021-04-01

6.  Automatic vasculature identification in coronary angiograms by adaptive geometrical tracking.

Authors:  Ruoxiu Xiao; Jian Yang; Mahima Goyal; Yue Liu; Yongtian Wang
Journal:  Comput Math Methods Med       Date:  2013-10-22       Impact factor: 2.238

7.  3D reconstruction of coronary artery bifurcations from coronary angiography and optical coherence tomography: feasibility, validation, and reproducibility.

Authors:  Wei Wu; Saurabhi Samant; Gijs de Zwart; Shijia Zhao; Behram Khan; Mansoor Ahmad; Marco Bologna; Yusuke Watanabe; Yoshinobu Murasato; Francesco Burzotta; Emmanouil S Brilakis; George Dangas; Yves Louvard; Goran Stankovic; Ghassan S Kassab; Francesco Migliavacca; Claudio Chiastra; Yiannis S Chatzizisis
Journal:  Sci Rep       Date:  2020-10-22       Impact factor: 4.379

  7 in total

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