BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
12/19/2019 10:34:37 AM | Browse: 844 | Download: 1479
 |
Received |
|
2019-07-19 13:53 |
|
Peer-Review Started |
|
2019-07-21 10:15 |
|
To Make the First Decision |
|
2019-09-23 00:56 |
|
Return for Revision |
|
2019-09-25 07:06 |
|
Revised |
|
2019-10-11 15:13 |
|
Second Decision |
|
2019-11-19 02:36 |
 |
Accepted by Journal Editor-in-Chief |
|
|
|
Accepted by Company Editor-in-Chief |
|
2019-11-21 19:22 |
|
Articles in Press |
|
2019-11-21 19:22 |
|
Publication Fee Transferred |
|
|
|
Edit the Manuscript by Language Editor |
|
|
|
Typeset the Manuscript |
|
2019-12-16 10:44 |
|
Publish the Manuscript Online |
|
2019-12-19 10:34 |
| ISSN |
1949-8470 (online) |
| Open Access |
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Radiology, Nuclear Medicine & Medical Imaging |
| Manuscript Type |
Observational Study |
| Article Title |
Segmentation of carotid arterial walls using neural networks
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Daniel D Samber, Sarayu Ramachandran, Anoop Sahota, Sonum Naidu, Alison Pruzan, Zahi A Fayad and Venkatesh Mani |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| American Heart Association Grant in Aid Founders Affiliate |
17GRNT33420119 |
| NIH NHLBI |
2R01HL070121 |
| NIH NHLBI |
1R01HL135878 |
|
| Corresponding Author |
Daniel D Samber, BSc, Research Scientist, Translational Molecular Imaging Institute (TMII), Icahn School of Medicine at Mount Sinai, 1470 Madison Avenue, New York, NY 10029, United States. daniel.samber@mssm.edu |
| Key Words |
Carotid arteries; Segmentation; Convolutional neural network; Magnetic resonance imaging; Vessel wall; |
| Core Tip |
Accurate segmentation of carotid arteries is useful in assessing the degree of heart disease in general and vascular diseases (such as atherosclerosis) in particular. Until recently, obtaining accurate segmentation could only be accomplished through the work of an experienced researcher requiring a large investment of time and effort. Over the last several years, the method of convolutional neural networks has demonstrated its efficacy in a number of fields. In this study, we apply this method to magnetic resonance images acquired from subjects with clinically evident atherosclerotic disease and compare the resulting segmentations with those determined by experienced researchers. |
| Publish Date |
2019-12-19 10:34 |
| Citation |
Samber DD, Ramachandran S, Sahota A, Naidu S, Pruzan A, Fayad ZA, Mani V. Segmentation of carotid arterial walls using neural networks. World J Radiol 2020; 12(1): 1-9 |
| URL |
https://www.wjgnet.com/1949-8470/full/v12/i1/1.htm |
| DOI |
https://dx.doi.org/10.4329/wjr.v12.i1.1 |
© 2004-2024 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
