About
Contact & Profiles
A5098907767
Research Areas
- Generative Adversarial Networks and Image Synthesis
- Cell Image Analysis Techniques
- Radiomics and Machine Learning in Medical Imaging
Universidad Rey Juan Carlos
2024
In the field of knee imaging, incorporation MR-based pseudo-CT synthesis holds potential to mitigate need for separate CT scans, simplifying workflows, enhancing patient comfort, and reducing radiation exposure. this work, we present a novel DL framework, grounded in development Cycle-Consistent Generative Adversarial Network (CycleGAN) method, tailored specifically images imaging surmount limitations current methods. Upon visually examining outcomes, it is evident that synthesized...
10.3390/app14114655
article
EN
cc-by
Applied Sciences
2024-05-28
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