The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …

The medical imaging literature has witnessed remarkable progress in high-performing
segmentation models based on convolutional neural networks. Despite the new …

The Segment Anything Model (SAM) has recently gained popularity in the field of image
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …

Abstract Diffusion Probabilistic Model (DPM) has recently become one of the hottest topics in
computer vision. Its image generation applications, such as Imagen, Latent Diffusion …

The Diffusion Probabilistic Model (DPM) has recently gained popularity in the field of
computer vision, thanks to its image generation applications, such as Imagen, Latent …

In medical image analysis, it is typical to collect multiple annotations, each from a different
clinical expert or rater, in the expectation that possible diagnostic errors could be mitigated …

Diabetic retinopathy (DR) is the most common cause of blindness in middle-aged people. It
shows that an automatic image evaluation system is needed in the diagnosis of this disease …

Abstract Domain adaptation typically requires to access source domain data to utilize their
distribution information for domain alignment with the target data. However, in many real …

Deep convolutional neural networks have significantly boosted the performance of fundus
image segmentation when test datasets have the same distribution as the training datasets …

Medical image segmentation plays a pivotal role in clinical diagnostics and treatment
planning, yet existing models often face challenges in generalization and in handling both …