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
The changes of postmortem corneal opacity are often used to roughly estimate the postmortem interval (PMI) in forensic practice. The difficulty associated with this time estimate is the lack of objective means to rapidly quantify postmortem corneal changes in crime scenes. This study constructed a data analysis model of PMI estimation and implemented an intelligent analysis system for examining the sequential changes of postmortem corneal digital images, named Corneal-Smart Phone, which can be used to quickly estimate PMI. The smart phone was used in combination with an attachment device that provided a darkroom environment and a steady light source to capture postmortem corneal images. By segmenting the corneal pupil region images, six color features, Red (R), Green (G), Blue (B), Hue (H), Saturation (S), Brightness (V) and four texture features Contrast (CON), Correlation (COR), Angular Second Moment (ASM), and Homogeneity (HOM), were extracted and correlated with PMI model. The results indicated that CON had the highest correlation with PMI (R = 0.983). No intra/intersubject variation in CON values were observed (p > 0.05). With the increase in ambient temperature or the decrease in humidity, the CON values were increased. PMI prediction error was <3 h within 36 h postmortem and extended to about 6-8 h after 36 h postmortem. The correct classification rate of the blind test samples was 82%. Our study provides a method that combines postmortem corneal image acquisition and digital image analysis to enable users to quickly obtain PMI estimation.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1111/1556-4029.14611 | DOI Listing |
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