Investigating the Performance of Generative Adversarial Networks for Prostate Tissue Detection and Segmentation

Investigating the Performance of Generative Adversarial Networks for Prostate Tissue Detection and Segmentation

The manual delineation of region of interest (RoI) in 3D magnetic resonance imaging (MRI) of the prostate is time-consuming and subjective. Correct identification of prostate tissue is helpful to define a precise RoI to be used in CAD systems in clinical practice during diagnostic imaging, radiother...

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Bibliographic Details
Main Authors: Ufuk Cem Birbiri, Azam Hamidinekoo, Amélie Grall, Paul Malcolm, Reyer Zwiggelaar
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Journal of Imaging
Subjects:
prostate MRI
computer aided diagnosis
segmentation
detection
generative adversarial network
Online Access:https://www.mdpi.com/2313-433X/6/9/83

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https://www.mdpi.com/2313-433X/6/9/83

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