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Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation
Automated computer-aided detection (CADe) in medical imaging has been an important tool in clinical practice and research. State-of-the-art methods often show high sensitivities but at the cost of high false-positives (FP) per patient rates. We design a two-tiered coarse-to-fine cascade framework th...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | IEEE Trans Med Imaging |
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| Κύριοι συγγραφείς: | , , , , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
2015
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7340334/ https://ncbi.nlm.nih.gov/pubmed/26441412 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2015.2482920 |
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