Generative adversarial networks (GANs) have become popular in medical imaging because of their remarkable performance and ability to translate images across ...

Similarly, it can be used for domain translation, such as MRI to CT conversion, to gain clear insights into disease-prone sections in less time, improving ...

Therefore, we conclude that the quantized model. (QEMCGAN), is a superior alternative to the previous models. F. Application to Medical Image Translation. In ...

A novel Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN (QEMCGAN) that employs evolutionary computation, multiobjective optimization, ...

The paper [20] proposes a novel Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN (QEMCGAN) to address issues faced by GANs in medical image-to- ...

Generative adversarial networks (GANs) have become popular in medical imaging because of their remarkable performance and ability to translate images across ...

Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN (QEMCGAN) is a recommended approach post-GAN for medical image processing, offering improved ...

... QEMCGAN: Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN for Medical Image Translation // IEEE Journal of Biomedical and Health Informatics.

A novel Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN (QEMCGAN) that employs evolutionary computation, multiobjective optimization, ...

Apr 21, 2021 · QEMCGAN: Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN for Medical Image Translation. Article. Apr 2023. Vandana Bharti ...