A Comparative Study of Generative Adversarial Networks in Medical Image Processing

The rapid development of Generative Adversarial Networks (GANs) has transformed medical image processing, enabling realistic image synthesis, augmentation, and restoration. This study presents a comparative evaluation of three representative GAN architectures, Pix2Pix, SPADE GAN, and Wasserstein GAN...

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Bibliographic Details
Published in:	Eng (Basel, Switzerland) Vol. 6; no. 11; p. 291
Main Authors:	Abdulqader, Marwa Mahfodh, Abdulazeez, Adnan Mohsin
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2025
Subjects:	Accuracy Brain Brain cancer Comparative studies Computer vision Datasets deep learning Generative adversarial networks Image processing Image segmentation Magnetic resonance imaging medical image Medical imaging MRI Realism segmentation Signal to noise ratio Synthesis Task complexity Tumors
ISSN:	2673-4117, 2673-4117
Online Access:	Get full text
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