Enhancing Medical Imaging with GANs Synthesizing Realistic Images from Limited Data-Reference-Cited by-同舟云学术

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Enhancing Medical Imaging with GANs Synthesizing Realistic Images from Limited Data

Published:2024-05-24 Issue: Volume: Page:1192-1197
ISSN:
Container-title:2024 IEEE 4th International Conference on Electronic Technology, Communication and Information (ICETCI)
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Author:

Feng Yinqiu¹,Zhang Bo²,Xiao Lingxi³,Yang Yutian⁴,Gegen Tana⁵,Chen Zexi⁶

Affiliation:

1. Columbia University,New York,USA

2. Texas Tech University,Lubbock,USA

3. Georgia Institue of Technology,Atlanta,USA

4. University of California, Davis,Davis,USA

5. Johns Hopkins University,Baltimore,USA

6. North Carolina State University,Raleigh,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10593799/10594004/10594540.pdf?arnumber=10594540

Reference28 articles.

1. Generative Adversarial Network for Medical Images (MI-GAN)

2. Nonsmooth nonconvex LDCT image reconstruction via learned descent algorithm

3. Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example

4. Research on Intelligent System of Multimodal Deep Learning in Image Recognition

5. Generative text-guided 3d vision-language pretraining for unified medical image segmentation;Chen,2023

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