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: 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
For common biomedical imaging facilities, such as CT, MRI, and confocal microscopy, the acquired scans are sequential parallel sections. The object of interest in each section image can be extracted by segmentation procedure to form serial parallel planar contours. How to reconstruct a trustworthy surface from these contours is a crucial issue in biomedical 3D visualization. In this paper, we propose an automatic, fast, and reliable surface reconstruction system. An improved correspondence-determining algorithm is proposed in the system to provide more reasonable contour-correspondences than the existing algorithms. It can handle more general input data, and does not produce wrong reconstruction results. A hybrid tiling algorithm is presented to tile the corresponding contours without the requirement of a contour-matching procedure. It can also handle the branching problem without any modification. For degenerate cases and branches, intermediate contours are introduced by means of contour interpolation to enhance the reconstruction results. The surface area and volume are also calculated to facilitate the practical applications.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.cmpb.2007.01.011 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!