Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&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: 3122
Function: getPubMedXML
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
Thermography captures the temperature distribution of the human skin and is employed in various medical applications. Often it is useful to cross-reference the resulting thermograms with visual images of the patient, either to see which part of the anatomy is affected by a certain disease or to judge the efficacy of the treatment. An attractive approach to provide this information is to overlay the two image types and show a composite image to the clinician. Producing such an overlay however is a non-trivial task due to differences in image capturing conditions of the two modalities. In this paper we introduce an approach that produces accurate overlays of thermal and visual medical images. First unnecessary background information of the visual part are removed by an image segmentation step based on skin detection. The thermal image is then aligned through an intensity based image registration technique. Experimental results based on an set of visual-thermal image pairs demonstrate the effectiveness of the proposed approach.
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Source |
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http://dx.doi.org/10.1109/IEMBS.2006.259275 | DOI Listing |
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