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Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment
OBJECTIVES: To simulate clinical deployment, evaluate performance, and establish quality assurance of a deep learning algorithm (U-Net) for detection, localization, and segmentation of clinically significant prostate cancer (sPC), ISUP grade group ≥ 2, using bi-parametric MRI. METHODS: In 2017, 284...
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| 出版年: | Eur Radiol |
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| 主要な著者: | , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer Berlin Heidelberg
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7755653/ https://ncbi.nlm.nih.gov/pubmed/32767102 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00330-020-07086-z |
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