Disease detection using medical images enables early and precise diagnosis. Despite the growing success of deep learning models, accurate classification remains a significant challenge. Medical images often exhibit characteristics such as limited spa...
Manual selection of optimal frames from kidney ultrasound videos is a time-consuming and subjective process that can introduce variability into clinical assessments. This study presents a fully automated deep learning-based framework designed to iden...
The segmentation accuracy of deep learning-based brain tumor MRI images still requires further improvement. We proposed a conditional diffusion network that incorporates image information into the mask's perturbed diffusion process. By optimizing the...
This study proposes a dual-branch framework for precise classification of breast tumor cellularity via histopathological images where it integrates two distinct branches: the Embedding Extraction Branch (embedding-driven) and the Vision Classificatio...
In this study, we present a novel hybrid model combining the Vision Transformer (ViT) and Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) for thyroid nodule detection in ultrasound images. While traditional methods, such a...
Accurate skin lesion segmentation is critical for improving early diagnosis of skin cancer. In this study, we propose AttenUNeT X, a novel extension of the U-Net architecture that integrates three key enhancements: (i) a feedback mechanism within dec...
The thyroid gland is prone to various diseases, including thyroid nodules. Ultrasound is the primary diagnostic tool, but classification accuracy is often limited by radiologist expertise. Integrating Artificial Intelligence, particularly Deep Learni...
Deep Learning methods have become a powerful tool in medical imaging, with great potential to improve diagnostic accuracy and support early disease detection. This is especially critical for breast cancer, one of the most common cancers among women, ...
Medical image segmentation is crucial in accurately diagnosing diseases and assisting physicians in examining relevant areas. Therefore, there is a pressing need for an artificial intelligence-based model that can facilitate the diagnostic process an...
Breast cancer detection and diagnosis remain challenging due to the complexity of tumor tissues and image quality variations, which hinder early and accurate identification. Timely diagnosis is vital for initiating treatment and improving patient out...
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