Automated and accurate segmentation of medical images is important for facilitating clinical
diagnosis and treatment. Currently, state-of-the-art (SOTA) diffusion based medical image …

Nowadays, denoising diffusion probabilistic models have been adapted for many image
segmentation tasks. However, existing end-to-end models have already demonstrated …

The core of medical image registration is the alignment of corresponding structures.
However, in multimodal image registration, substantial differences in appearance (intensity …

Background In clinical diagnostics, magnetic resonance imaging (MRI) technology plays a
crucial role in the recognition of cardiac regions, serving as a pivotal tool to assist physicians …

Diffusion models have made great success in image generation and own much potential in
other vision tasks like image segmentation. With respect to medical image segmentation …

The ability to predict multiple potential outputs for a single input can significantly address
visual ambiguity, such as diverse semantic segmentation annotations for a medical image …

Denoising Diffusion Probabilistic Models (DDPMs) have garnered significant interest due to
their notable capabilities in image generation. The models could used for lesion …

Small object detection has always been one of the most challenging tasks in the computer
vision. Up to now, a prior bounding box is often applied to Unmanned Aerial Vehicle (UAV) …

Small object detection has always been one of the most challenging tasks in the computer
vision. Up to now, a prior bounding box is often applied to Unmanned Aerial Vehicle (UAV) …

Background: Breast cancer diagnosis relies on accurate lesion segmentation in medical
images. Automated computer-aided diagnosis reduces clinician workload and improves …