… We note that in medical image segmentation tasks, lesions/organs are often ambiguous and
difficult to discriminate … We design our model based on diffusion model proposed in (Ho et al.…

… is a challenging task with inherent ambiguity and high uncertainty attributed to factors such
… masks in segmentation. To achieve accurate and diverse medical image segmentation masks…

… Second, we propose a novel binary Bernoulli diffusion model (BBDM) as the diffusion refiner…
space that makes it challenging to handle ambiguous boundaries and subtle objects. To …

… segmentation method based on diffusion models. … diffusion models can perform lesion
segmentation of medical images. To generate an image-specific segmentation, we train the model …

… images, where organs or lesions commonly have ambiguous boundaries. However, it is worth
… As the first transformer-based diffusion model for medical image segmentation, we believe …

… , we use diffusion models to solve the image segmentation problem as conditional generation,
given the image. … , I., Patel, VM: Ambiguous medical image segmentation using diffusion …

… Furthermore, we emphasize the practical use case of some selected approaches, and then
we discuss the limitations of the diffusion models in the medical domain and propose several …

… The main focus of the approach consists on the use of contextual possibilistic knowledge in
… the ambiguous zones. Therefore, this knowledge updating intends to reduce the ambiguity …

… image segmentation method to tackle two critical problems of medical image, which are (i)
ambiguity of … Probabilistic diffusion for interactive image segmentation. IEEE Transactions on …

… However, medical image classification is particularly challenging due to the ambiguity of …
The diffusion model in this study leverages a standard DDPM training process, where the …