Literature DB >> 22257909

3D segmentation of abdominal aorta from CT-scan and MR images.

Anthony Adam Duquette1, Pierre-Marc Jodoin, Olivier Bouchot, Alain Lalande.   

Abstract

We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maximum aortic diameter, the volume overlap and the Hausdorff distance) the variability of the results obtained by our method is shown to be similar to that of a human operator, both for the lumen interface and the aortic wall. As will be shown, the average distance obtained with our method is less than one standard deviation away from each expert, both for healthy subjects and for patients with AAA. Our semi-automatic method provides reliable contours of the abdominal aorta from CT-scan or MRI, allowing rapid and reproducible evaluations of AAA.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22257909     DOI: 10.1016/j.compmedimag.2011.12.001

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  10 in total

1.  Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

Authors:  Toshiyuki Okada; Marius George Linguraru; Masatoshi Hori; Ronald M Summers; Noriyuki Tomiyama; Yoshinobu Sato
Journal:  Med Image Anal       Date:  2015-07-04       Impact factor: 8.545

2.  Iterative reconstruction in single-source dual-energy CT angiography: feasibility of low and ultra-low volume contrast medium protocols.

Authors:  Ping Hou; Xiangnan Feng; Jie Liu; Yue Zhou; Yaojun Jiang; Xiaochen Jiang; Jianbo Gao
Journal:  Br J Radiol       Date:  2017-06-23       Impact factor: 3.039

3.  A hybrid method based on fuzzy clustering and local region-based level set for segmentation of inhomogeneous medical images.

Authors:  Maryam Rastgarpour; Jamshid Shanbehzadeh; Hamid Soltanian-Zadeh
Journal:  J Med Syst       Date:  2014-06-24       Impact factor: 4.460

4.  Automatic segmentation of the aortic root in CT angiography of candidate patients for transcatheter aortic valve implantation.

Authors:  M A Elattar; E M Wiegerinck; R N Planken; E Vanbavel; H C van Assen; J Baan; H A Marquering
Journal:  Med Biol Eng Comput       Date:  2014-06-06       Impact factor: 2.602

5.  Automatic Detection and Segmentation of Thrombi in Abdominal Aortic Aneurysms Using a Mask Region-Based Convolutional Neural Network with Optimized Loss Functions.

Authors:  Byunghoon Hwang; Jihu Kim; Sungmin Lee; Eunyoung Kim; Jeongho Kim; Younhyun Jung; Hyoseok Hwang
Journal:  Sensors (Basel)       Date:  2022-05-10       Impact factor: 3.847

6.  Fully automated multiorgan segmentation in abdominal magnetic resonance imaging with deep neural networks.

Authors:  Yuhua Chen; Dan Ruan; Jiayu Xiao; Lixia Wang; Bin Sun; Rola Saouaf; Wensha Yang; Debiao Li; Zhaoyang Fan
Journal:  Med Phys       Date:  2020-08-30       Impact factor: 4.071

7.  The ascending aortic image quality and the whole aortic radiation dose of high-pitch dual-source CT angiography.

Authors:  Ying Liu; Jian Xu; Jian Li; Jing Ren; Hongtao Liu; Junqing Xu; Mengqi Wei; Yuewen Hao; Minwen Zheng
Journal:  J Cardiothorac Surg       Date:  2013-12-12       Impact factor: 1.637

8.  A fully automated pipeline for mining abdominal aortic aneurysm using image segmentation.

Authors:  Fabien Lareyre; Cédric Adam; Marion Carrier; Carine Dommerc; Claude Mialhe; Juliette Raffort
Journal:  Sci Rep       Date:  2019-09-24       Impact factor: 4.379

9.  Automated Delineation of Vessel Wall and Thrombus Boundaries of Abdominal Aortic Aneurysms Using Multispectral MR Images.

Authors:  B Rodriguez-Vila; J Tarjuelo-Gutierrez; P Sánchez-González; P Verbrugghe; I Fourneau; G Maleux; P Herijgers; E J Gomez
Journal:  Comput Math Methods Med       Date:  2015-07-05       Impact factor: 2.238

10.  High-pitch, low-voltage and low-iodine-concentration CT angiography of aorta: assessment of image quality and radiation dose with iterative reconstruction.

Authors:  Yanguang Shen; Zhonghua Sun; Lei Xu; Yu Li; Nan Zhang; Zixu Yan; Zhanming Fan
Journal:  PLoS One       Date:  2015-02-02       Impact factor: 3.240

  10 in total

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