Texture analysis and multiple-instance learning for the classification of malignant lymphomas
Highlights • Malignant lymphomas subtype classification with machine learning. • Texture features extracted from FDG-PET volumes of interest. • Multiple-instance learning SVM for patient-level categorization. • Random forests exploited for feature selection.
Gespeichert in:
| Autor*in: |
Lippi, Marco [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Dynamic measurement of stay-cable force using digital image techniques - Du, Wenkang ELSEVIER, 2019, an international journal devoted to the development, implementation and exchange of computing methodology and software systems in biomedical research and medical practice, Amsterdam |
|---|---|
| Übergeordnetes Werk: |
volume:185 ; year:2020 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.cmpb.2019.105153 |
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ELV049389130 |
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10.1016/j.cmpb.2019.105153 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000912.pica (DE-627)ELV049389130 (ELSEVIER)S0169-2607(19)30205-6 DE-627 ger DE-627 rakwb eng 660 VZ 50.21 bkl Lippi, Marco verfasserin aut Texture analysis and multiple-instance learning for the classification of malignant lymphomas 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Highlights • Malignant lymphomas subtype classification with machine learning. • Texture features extracted from FDG-PET volumes of interest. • Multiple-instance learning SVM for patient-level categorization. • Random forests exploited for feature selection. Gianotti, Stefania oth Fama, Angelo oth Casali, Massimiliano oth Barbolini, Elisa oth Ferrari, Angela oth Fioroni, Federica oth Iori, Mauro oth Luminari, Stefano oth Menga, Massimo oth Merli, Francesco oth Trojani, Valeria oth Versari, Annibale oth Zanelli, Magda oth Bertolini, Marco oth Enthalten in Elsevier Du, Wenkang ELSEVIER Dynamic measurement of stay-cable force using digital image techniques 2019 an international journal devoted to the development, implementation and exchange of computing methodology and software systems in biomedical research and medical practice Amsterdam (DE-627)ELV003255476 volume:185 year:2020 pages:0 https://doi.org/10.1016/j.cmpb.2019.105153 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 50.21 Messtechnik VZ AR 185 2020 0 |
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Highlights • Malignant lymphomas subtype classification with machine learning. • Texture features extracted from FDG-PET volumes of interest. • Multiple-instance learning SVM for patient-level categorization. • Random forests exploited for feature selection. |
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Highlights • Malignant lymphomas subtype classification with machine learning. • Texture features extracted from FDG-PET volumes of interest. • Multiple-instance learning SVM for patient-level categorization. • Random forests exploited for feature selection. |
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