Deep Learning of MR Imaging Patterns in Prostate Cancer
Nelly Tan1, Noah Stier1, Steven Raman1, and Fabien Scalzo1
1UCLA, Los Angeles, CA, United States
This demonstrates the feasibility of using Deep Learning to characterize prostate cancer lesions in an automatic fashion. The translation and development of this method into a decision support tool may provide more objective criteria for clinicians during diagnosis.
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