most citedUSE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets

1 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2019★ 1 cited

USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets

Leonardo Rundo, Changhee Han, Yudai Nagano +12

Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, th…

cs.CV2019★ 1 cited

CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study

Leonardo Rundo, Changhee Han, Jin Zhang +10

Prostate cancer is the most common cancer among US men. However, prostate imaging is still challenging despite the advances in multi-parametric Magnetic Resonance Imaging (MRI), wh…