Literature DB >> 21880391

Geometrical methods for level set based abdominal aortic aneurysm thrombus and outer wall 2D image segmentation.

Christos Zohios1, Georgios Kossioris, Yannis Papaharilaou.   

Abstract

Abdominal aortic aneurysm (AAA) is a localized dilatation of the aortic wall. Accurate measurements of its geometric characteristics are critical for a reliable estimate of AAA rupture risk. However, current imaging modalities do not provide sufficient contrast to distinguish thrombus from surrounding tissue thus making the task of segmentation quite challenging. The main objective of this paper is to address this problem and accurately extract the thrombus and outer wall boundaries from cross sections of a 3D AAA image data set (CTA). This is achieved by new geometrical methods applied to the boundary curves obtained by a Level Set Method (LSM). Such methods address the problem of leakage of a moving front into sectors of similar intensity and that of the presence of calcifications. The versatility of the methods is tested by creating artificial images which simulate the real cases. Segmentation quality is quantified by comparing the results with a manual segmentation of the slices of ten patient data sets. Sensitivity to the parameter settings and reproducibility are analyzed. This is the first work to our knowledge that utilizes the level set framework to extract both the thrombus and external AAA wall boundaries.
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21880391     DOI: 10.1016/j.cmpb.2011.06.009

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  6 in total

1.  Generic thrombus segmentation from pre- and post-operative CTA.

Authors:  Florent Lalys; Vincent Yan; Adrien Kaladji; Antoine Lucas; Simon Esneault
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-04-28       Impact factor: 2.924

2.  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

3.  Quantitative Aortic Distensibility Measurement Using CT in Patients with Abdominal Aortic Aneurysm: Reproducibility and Clinical Relevance.

Authors:  Yunfei Zha; Gongling Peng; Liang Li; Chunying Yang; Xuesong Lu; Zhoufeng Peng
Journal:  Biomed Res Int       Date:  2017-04-18       Impact factor: 3.411

4.  Development and Comparison of Multimodal Models for Preoperative Prediction of Outcomes After Endovascular Aneurysm Repair.

Authors:  Yonggang Wang; Min Zhou; Yong Ding; Xu Li; Zhenyu Zhou; Zhenyu Shi; Weiguo Fu
Journal:  Front Cardiovasc Med       Date:  2022-04-26

5.  Evaluation of a hybrid pipeline for automated segmentation of solid lesions based on mathematical algorithms and deep learning.

Authors:  Liam Burrows; Ke Chen; Weihong Guo; Martin Hossack; Richard G McWilliams; Francesco Torella
Journal:  Sci Rep       Date:  2022-08-20       Impact factor: 4.996

6.  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

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.