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
We present here a direct least-squares estimation (DLSE) method for the determination of renal kinetic parameters from sequences of very fast acquisitions performed with a three-headed single photon emission computed tomography (SPECT) system. A simple linear model for the behavior of the radiopharmaceutical, as well as a spatial model for its spatial distribution are defined. The model enables one to estimate the kinetic parameters directly from the projections, once the plasma concentration function is known. A new technique for the accurate reconstruction of time-radioactivity curves based on the direct reconstruction of the region-of-interest contents from a series of data from three-projections is presented. The technique is used to determine the plasma concentration function with a sub-second time resolution. The spatially-variant geometrical response is also included in the model to compensate for the spatial resolution of the SPECT system. Results obtained from simulations are presented. Basic spatial and time features of the simulations are derived from a patient study. Noise and segmentation errors are also simulated. The DLSE method is compared with the conventional one of deriving kinetic parameters from the time series of reconstructed images. The standard deviation of results given by DLSE is less than 2%, whereas with the conventional method it is between 5% and 6%. Within the limit of statistical fluctuations, DLSE results are unbiased whereas those of the conventional method are overestimated by 24%.
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Source |
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http://dx.doi.org/10.1109/TMI.2004.824149 | DOI Listing |
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