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
This article presents 582 bone scan images from 291 adult patients who attended the Nuclear Medicine Service at the Instituto de Investigaciones en Ciencias de la Salud (IICS) of the Universidad Nacional de Asunción (UNA), Paraguay, between 2020 and 2024. The images were acquired using trimodal SPECT-CT-PET equipment, model AnyScan SCP, and the MEDISO brand. Approximately 20 mCi of technetium-99m methylene diphosphonate (Tc-MDP) was administered to each patient, producing whole-body planar images in anterior and posterior projections of the axial and appendicular skeleton with a resolution of 256 × 1024 pixels. The images were labeled according to the final diagnosis by a nuclear physician, covering conditions ranging from joint lesions to bone metastases. This dataset will be helpful for researchers working on bone scan image analysis using artificial intelligence techniques to classify bone metastases.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11699483 | PMC |
http://dx.doi.org/10.1016/j.dib.2024.111191 | DOI Listing |
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