Are deep models in radiomics performing better than generic models? A systematic review
Abstract Background Application of radiomics proceeds by extracting and analysing imaging features based on generic morphological, textural, and statistical features defined by formulas. Recently, deep learning methods were applied. It is unclear whether deep models (DMs) can outperform generic mode...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-03-01
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| Series: | European Radiology Experimental |
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| Online Access: | https://doi.org/10.1186/s41747-023-00325-0 |