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
Image cytometry has numerous clinical and research applications and is particularly useful in anatomic pathology for the study of malignant lesions. Modern image systems encompass morphometry, densitometry, neural networks, and expert systems. Rapid advances in technology and the development of user-friendly systems have provided pathologists with an alternative to flow cytometry, particularly useful in the evaluation of small or hypocellular specimens. The most common current application of image cytometry is for DNA analysis, followed by quantitation of immunohistochemical staining. Newer uses under active investigation include development of expert systems that may act as diagnostic consultants in the future. Beyond DNA analysis, image cytometry holds great promise for improved tumor classification, for screening and surveillance in high-risk populations, and as a tool to improve diagnostic ability. This article discusses types of image analysis systems, specimen preparation, data acquisition, current applications in specific organ sites, and possible future applications.
Download full-text PDF |
Source |
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http://dx.doi.org/10.3109/10408369409084672 | DOI Listing |
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