The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classificati...
The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classification Tested on Different Datasets That Are Not Derived from LIDC-IDRI: A Systematic Review
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Switzerland: MDPI AG
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Language
English
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Switzerland: MDPI AG
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The aim of this study was to systematically review the performance of deep learning technology in detecting and classifying pulmonary nodules on computed tomography (CT) scans that were not from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) database. Furthermore, we explored the difference in performance when...
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Full title
The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classification Tested on Different Datasets That Are Not Derived from LIDC-IDRI: A Systematic Review
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6963966
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6963966
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ISSN
2075-4418
E-ISSN
2075-4418
DOI
10.3390/diagnostics9040207
