To ensure a fair comparison with Mostafa’s proposed CAE model, we maintained consistency in data processing, using T1-weighted MRI slice images of the healthy control group for autoencoder ...

Deep generative models, such as generative adversarial network (GAN) and variational autoencoder (VAE), have been utilized extensively for medical image generation. While these models made remarkable ...

Regularized autoencoders learn the latent codes, a structure with the regularization under the distribution, which enables them the capability to infer the latent codes given observations and generate ...

This project leverages SAM 2.0's advanced segmentation capabilities to automate the creation of annotated datasets. The system significantly reduces the time and effort required for manual annotation, ...

However, in the medical imaging domain, annotated datasets for specific tasks are often small due to the high complexity of annotations, limited access, or the rarity of diseases. To address this ...