Jan 25, 2023 · To solve these problems, we propose a novel deep learning model where a frequent pattern mining component and an adversarial-based denoising autoencoder component are introduced. Extensive experiments are conducted on a real retinal image dataset to evaluate the performance of the proposed model.

Mar 1, 2024 · To address these issues, we proposed the AE-COT-GAN model (Autoencoder-based Conditional Optimal Transport Generative Adversarial Network) for the generation of medical images belonging to specific categories. The training process of our model comprises three fundamental components.

Nov 11, 2024 · This study reviews important architectures and methods used to develop VAEs for medical images and provides a comparison with other generative models such as GANs on issues such as image quality, and low diversity of generated samples.

May 5, 2025 · The study’s results show the potential of GANs in detecting anomalies in medical images with high precision and accuracy. This approach can potentially be used in clinical settings to detect anomalies in medical images early, thereby improving patient outcomes.

Sep 1, 2022 · To solve these problems, we propose a novel deep learning model where a frequent pattern mining component and an adversarial-based denoising autoencoder component are introduced. Extensive...

Dec 10, 2024 · Learn about key techniques, tools, and best practices used to annotate medical images accurately, and explore how AI and human collaboration enhance the quality and efficiency of medical data labeling.

One of the crucial initial steps in biomedical image processing and analysis is image denoising as improved visual quality of images may increase the accuracy of medical diagnosis and image preprocessing is required at the input for analytical methods like …

Jan 1, 2022 · Autoencoders and variational autoencoders are powerful tools with widespread applications in biomedical image analysis and synthesis [2], [3], [4]. Because of the low-dimensional data representation and the ability to generate new, unseen data, they are ideal tools for image synthesis tasks.

Mar 10, 2022 · Masked Autoencoder (MAE) has recently been shown to be effective in pre-training Vision Transformers (ViT) for natural image analysis. By reconstructing full images from partially masked inputs, a ViT encoder aggregates contextual information to …

21 hours ago · Medical image annotation plays a key role in the healthcare data annotation market. The global data annotation market was valued at $629.5 million in 2021 and is projected to grow at a CAGR of 26.6% from 2022 to 2030 .