Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Automatic calcification detection in abdominal aorta consists of a set of computer vision techniques to quantify the amount of calcium that is found around this artery. Knowing that information, it is possible to perform statistical studies that relate vascular diseases with the presence of calcium in these structures. To facilitate the detection in CT images, a contrast is usually injected into the circulatory system of the patients to distinguish the aorta from other body tissues and organs. This contrast increases the absorption of X-rays by human blood, making it easier the measurement of calcifications. Based on this idea, a new system capable of detecting and tracking the aorta artery has been developed with an estimation of the calcium found surrounding the aorta. Besides, the system is complemented with a 3D visualization mode of the image set which is designed for the new generation of immersive VR devices.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1109/EMBC.2016.7591642 | DOI Listing |
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