Convolutional Neural Networks for Prostate Magnetic Resonance Image Segmentation

Convolutional Neural Networks for Prostate Magnetic Resonance Image Segmentation

One of the most accurate and non-invasive prostate imaging methods is magnetic resonance imaging (MRI). Segmentation is needed to find the boundary of the prostate, either automatically or semi-automatically. Recently, fully convolutional neural networks (FCNN) are being used for this purpose. In th...

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Bibliographic Details
Main Authors:	Tahereh Hassanzadeh, Leonard G. C. Hamey, Kevin Ho-Shon
Format:	Article
Language:	English
Published:	IEEE 2019-01-01
Series:	IEEE Access
Subjects:	Automatic MRI segmentation fully convolutional neural network prostate MRI segmentation
Online Access:	https://ieeexplore.ieee.org/document/8666973/

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