Skin lesion segmentation is a computer-aided diagnosis method for quantitative analysis of
melanoma that can improve efficiency and accuracy. Although many methods based on U …

Gastrointestinal (GI) cancer is a malignancy affecting the digestive organs. During radiation
therapy, the radiation oncologist must precisely aim the X-ray beam at the tumor while …

Medical image segmentation is widely used in clinical diagnosis, and methods based on
convolutional neural networks have been able to achieve high accuracy. However, it is still …

Deep learning architectures based on convolutional neural network (CNN) and Transformer
have achieved great success in medical image segmentation. Models based on the encoder …

Colonoscopy is considered the gold standard for colorectal cancer diagnosis and prognosis.
However, existing methods are less accurate and prone to overlooking lesions during …

Automatic segmentation of skin lesions is beneficial for improving the accuracy and
efficiency of melanoma diagnosis. However, due to variation in the size and shape of the …

Accurate medical image segmentation is of great significance for subsequent diagnosis and
analysis. The acquisition of multi-scale information plays an important role in segmenting …

Brain tumor segmentation has been a challenging and popular research problem in the area
of medical imaging and computer-aided diagnosis. In the last few years, especially since …

In the current era, diffusion models have emerged as a groundbreaking force in the realm of
medical image segmentation. Against this backdrop, we introduce the Diffusion Text …

Colorectal cancer is one of the leading causes of death worldwide. Polyps are early
symptoms of colorectal cancer and prone to malignant transformation. Polyp segmentation …