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
The wall-filter selection curve method is proposed to objectively identify a cut-off velocity that minimizes artifacts in power Doppler images. A selection curve, which is constructed by plotting the color pixel density (CPD) as a function of the cut-off velocity, exhibits characteristic intervals hypothesized to include the optimum cut-off velocity. This article presents an improved implementation of the method that automatically detects characteristic intervals in a selection curve and selects an operating point cut-off velocity along a characteristic interval. The method is applied to subregions within the Doppler image to adapt the cut-off velocity to local variations in vascularity. The method's performance is evaluated in 30-MHz power Doppler images of a four-vessel flow phantom. At high (>5 mm/s) flow velocities, qualitative improvements in vessel delineation are achieved and the CPD in the resulting images is accurate to within 3% of the vascular volume fraction of the phantom.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.ultrasmedbio.2012.03.017 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!