• Corpus ID: 226226750

Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI

  title={Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI},
  author={Anindo Saha and Matin Hosseinzadeh and Henkjan J. Huisman},
We hypothesize that anatomical priors can be viable mediums to infuse domain-specific clinical knowledge into state-of-the-art convolutional neural networks (CNN) based on the U-Net architecture. We introduce a probabilistic population prior which captures the spatial prevalence and zonal distinction of clinically significant prostate cancer (csPCa), in order to improve its computer-aided detection (CAD) in bi-parametric MR imaging (bpMRI). To evaluate performance, we train 3D adaptations of… 

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