Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

In the realm of medical image segmentation, both CNN-based and Transformer-based
models have been extensively explored. However, CNNs exhibit limitations in long-range …

Transformer and its variants have been widely used for medical image segmentation.
However, the large number of parameter and computational load of these models make …

State Space Model (SSM) is a mathematical model used to describe and analyze the
behavior of dynamic systems. This model has witnessed numerous applications in several …

Skin cancer diagnosis often relies on image segmentation as a crucial aid, and a high-
performance segmentation can lower misdiagnosis risks. Part of the medical devices often …

In recent years, continuous latent space (CLS) and discrete latent space (DLS) deep
learning models have been proposed for medical image analysis for improved performance …

Traditionally for improving the segmentation performance of models, most approaches
prefer to use adding more complex modules. And this is not suitable for the medical field …

In the field of medical image segmentation, models based on both CNN and Transformer
have been thoroughly investigated. However, CNNs have limited modeling capabilities for …

In recent years, dermoscopy, as a noninvasive means of detection, has been increasingly
used in the auxiliary diagnosis of skin disease, especially for skin cancer, such as malignant …

In this paper, we introduce U-Net v2, a new robust and efficient U-Net variant for medical
image segmentation. It aims to augment the infusion of semantic information into low-level …