Загрузка...
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...
Сохранить в:
| Опубликовано в: : | IEEE Trans Med Imaging |
|---|---|
| Главные авторы: | , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2015
|
| Предметы: | |
| Online-ссылка: | 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 |
| Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|