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
No one can deny the significant impact of artificial intelligence (AI) on everyday life, especially in the health sector where it has emerged as a crucial and beneficial tool in Nuclear Medicine (NM) and molecular imaging. The objective of this review is to provide a summary of the various applications of AI in single-photon emission computed tomography (SPECT) and positron emission tomography (PET), with or without anatomical information (CT or magnetic resonance imaging (MRI)). This review analyzes subsets of AI, such as machine learning (ML) and Deep Learning (DL), and elaborates on their applications in NM imaging (NMI) physics, including the generation of attenuation maps, estimation of scattered events, depth of interaction (DOI), time of flight (TOF), NM image reconstruction (optimization of the reconstruction algorithm), and low dose imaging.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1967/s002449912561 | DOI Listing |
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