The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …

Medical image segmentation has seen significant improvements with transformer models,
which excel in grasping far-reaching contexts and global contextual information. However …

While CNN-based methods have been the cornerstone of medical image segmentation due
to their promising performance and robustness, they suffer from limitations in capturing long …

Cell localization in medical image analysis is a challenging task due to the significant
variation in cell shape, size and color. Existing localization methods continue to tackle these …

Abstract The Segment Anything Model (SAM) has garnered significant attention for its
versatile segmentation abilities and intuitive prompt-based interface. However its application …

Abstract While the Segment Anything Model (SAM) excels in semantic segmentation for
general-purpose images, its performance significantly deteriorates when applied to medical …

Convolutional neural networks (CNN), especially U-shaped networks, have become the
mainstream approach for medical image segmentation. However, due to the intrinsic locality …

Identifying and managing osteosarcoma pose significant challenges, especially in resource-
constrained developing nations. Advanced diagnostic methods involve isolating the nucleus …

In recent years, denoising diffusion models have achieved remarkable success in
generating pixel-level representations with semantic values for image generation modeling …