9 citations · 14 across the 4 of their papers we have counts for
4 papers
Federated Learning with Research Prototypes for Multi-Center MRI-based Detection of Prostate Cancer with Diverse Histopathology
Abhejit Rajagopal, Ekaterina Redekop, Anil Kemisetti +5
Early prostate cancer detection and staging from MRI are extremely challenging tasks for both radiologists and deep learning algorithms, but the potential to learn from large and d…
CAT-Net: A Cross-Slice Attention Transformer Model for Prostate Zonal Segmentation in MRI
Alex Ling Yu Hung, Haoxin Zheng, Qi Miao +3
Prostate cancer is the second leading cause of cancer death among men in the United States. The diagnosis of prostate MRI often relies on the accurate prostate zonal segmentation.…
Automatic Prostate Zonal Segmentation Using Fully Convolutional Network with Feature Pyramid Attention
Yongkai Liu, Guang Yang, Sohrab Afshari Mirak +7
Our main objective is to develop a novel deep learning-based algorithm for automatic segmentation of prostate zone and to evaluate the proposed algorithm on an additional independe…
Prostate cancer inference via weakly-supervised learning using a large collection of negative MRI
Ruiming Cao, Xinran Zhong, Fabien Scalzo +2
Recent advances in medical imaging techniques have led to significant improvements in the management of prostate cancer (PCa). In particular, multi-parametric MRI (mp-MRI) continue…