Year: 2024
Type: article
Abstract: Generative Adversarial Networks (GANs) have shown promising prospects and achieved significant results in medical image analysis tasks. This article provides a comprehensive review of recent research on GANs and their variants in medical applications, including tasks such as image synthesis, segmentation, classification, detection, denoising, reconstruction, fusion, registration, and prediction. We summarize and analyze the reviewed literature, with a focus on model framework design,dataset sources, and performance evaluation. Our research findings are presented in the form of tables. In the end,article discusses open challenges and directions for future research.
Source: Artificial Intelligence Review
Authors: Yang Heng, Ma Yinghua, Fiaz Gul Khan, Ahmad Khan, Farman Ali, Ahmad Ali AlZubi, Zeng Hui
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
Funder: King Saud University
Award: G5765226443
OpenAlex ID: W4405654368