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
In acne treatment, it is important to accurately evaluate the severity of Acne. The acne should be classified into several skin lesions including comedo, reddish papule, pustule, and scar. However, in some cases, a visual detection from RGB image maybe difficult for the proper evaluation of acne skin lesions. This paper proposes an extraction method using the spectral information of the various type of acne skin lesions calculated from the multispectral images (MSI) of the lesions. In the experiment, we showed the possibility of classifying acne lesion types by applying a combination of several linear discriminant functions (LDF's).
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Source |
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http://dx.doi.org/10.1109/IEMBS.2008.4650105 | DOI Listing |
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