Training Convolutional Networks for Prostate Segmentation With Limited Data

Training Convolutional Networks for Prostate Segmentation With Limited Data

Multi-zonal segmentation is a critical component of computer-aided diagnostic systems for detecting and staging prostate cancer. Previously, convolutional neural networks such as the U-Net have been used to produce fully automatic multi-zonal prostate segmentation on magnetic resonance images (MRIs)...

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Bibliographic Details
Main Authors: Sara L. Saunders, Ethan Leng, Benjamin Spilseth, Neil Wasserman, Gregory J. Metzger, Patrick J. Bolan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Automatic prostate segmentation
magnetic resonance imaging
convolutional neural networks
3D U-Net
Online Access:https://ieeexplore.ieee.org/document/9499065/

Internet

https://ieeexplore.ieee.org/document/9499065/

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