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: 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
Accurate patient registration and referencing is a key element in navigated surgery. Unfortunately all existing methods are either invasive or very time consuming. We propose a fully non-invasive optical approach using a tracked monocular endoscope to reconstruct the surgical scene in 3D using photogrammetric methods. The 3D reconstruction can then be used for matching the pre-operative data to the intra-operative scene. In order to cope with the near real-time requirements for referencing, we use a novel, efficient 3D point management method during 3D model reconstruction. The presented prototype system provides a reconstruction accuracy of 0.1 mm and a tracking accuracy of 0.5 mm on phantom data. The ability to cope with real data is demonstrated by cadaver experiments.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/11866565_100 | DOI Listing |
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