Editorial for "A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion"
- PMID: 33813780
- DOI: 10.1002/jmri.27630
Editorial for "A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion"
Comment on
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A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion.J Magn Reson Imaging. 2021 Aug;54(2):462-471. doi: 10.1002/jmri.27599. Epub 2021 Mar 14. J Magn Reson Imaging. 2021. PMID: 33719168 Free PMC article.
References
-
- Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA Cancer J Clin 2021;71(1):7-33.
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- Harvey CJ, Pilcher J, Richenberg J, Patel U, Frauscher F. Applications of transrectal ultrasound in prostate cancer. Brit J Radiol 2012;85: Spec No 1:S3-17.
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- Ahmed HU, Bosaily AES, Brown LC, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): A paired validating confirmatory study. Lancet 2017;389(10071):815-822.
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- Dickinson L, Ahmed HU, Allen C, et al. Magnetic resonance imaging for the detection, localisation, and characterisation of prostate cancer: Recommendations from a European consensus meeting. Eur Urol 2011;59(4):477-494.
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- Kasivisvanathan V, Rannikko AS, Borghi M, et al. MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med 2018;378(19):1767-1777.
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