Literature DB >> 20655274

Segmentation and reconstruction of vascular structures for 3D real-time simulation.

Xunlei Wu1, Vincent Luboz, Karl Krissian, Stephane Cotin, Steve Dawson.   

Abstract

We propose a technique to obtain accurate and smooth surfaces of patient specific vascular structures, using two steps: segmentation and reconstruction. The first step provides accurate and smooth centerlines of the vessels, together with cross section orientations and cross section fitting. The initial centerlines are obtained from a homotopic thinning of the vessels segmented using a level set method. In addition to circle fitting, an iterative scheme fitting ellipses to the cross sections and correcting the centerline positions is proposed, leading to a strong improvement of the cross section orientations and of the location of the centerlines. The second step consists of reconstructing the surface based on this data, by generating a set of topologically preserved quadrilateral patches of branching tubular structures. It improves Felkel's meshing method (Felkel et al., 2004) by: allowing a vessel to have multiple parents and children, reducing undersampling artifacts, and adapting the cross section distribution. Experiments, on phantom and real datasets, show that the proposed technique reaches a good balance in terms of smoothness, number of triangles, and distance error. This technique can be applied in interventional radiology simulations, virtual endoscopy and in reconstruction of smooth and accurate three-dimensional models for use in simulation.
Copyright © 2010 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 20655274     DOI: 10.1016/j.media.2010.06.006

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


  6 in total

1.  Carotid vasculature modeling from patient CT angiography studies for interventional procedures simulation.

Authors:  M Freiman; L Joskowicz; N Broide; M Natanzon; E Nammer; O Shilon; L Weizman; J Sosna
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-02-29       Impact factor: 2.924

2.  Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface.

Authors:  Shinjiro Miyawaki; Merryn H Tawhai; Eric A Hoffman; Sally E Wenzel; Ching-Long Lin
Journal:  Biomech Model Mechanobiol       Date:  2016-10-04

3.  Scale-adaptive surface modeling of vascular structures.

Authors:  Jianhuang Wu; Mingqiang Wei; Yonghong Li; Xin Ma; Fucang Jia; Qingmao Hu
Journal:  Biomed Eng Online       Date:  2010-11-19       Impact factor: 2.819

4.  Accelerating cardiovascular model building with convolutional neural networks.

Authors:  Gabriel Maher; Nathan Wilson; Alison Marsden
Journal:  Med Biol Eng Comput       Date:  2019-08-24       Impact factor: 2.602

5.  Fully automatic deep learning trained on limited data for carotid artery segmentation from large image volumes.

Authors:  Tianshu Zhou; Tao Tan; Xiaoyan Pan; Hui Tang; Jingsong Li
Journal:  Quant Imaging Med Surg       Date:  2021-01

6.  3D vasculature segmentation using localized hybrid level-set method.

Authors:  Qingqi Hong; Qingde Li; Beizhan Wang; Yan Li; Junfeng Yao; Kunhong Liu; Qingqiang Wu
Journal:  Biomed Eng Online       Date:  2014-12-16       Impact factor: 2.819

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.