The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …

Recommender systems are widely adopted as an increasing research and development
area, since they provide users with diverse and useful information tailored to their needs …

Medical image segmentation is a crucial task in computer-aided diagnosis. While deep
learning has significantly improved this field, relying solely on local computing power makes …

Cervical cancer is the fourth most common cancer worldwide, and early diagnosis is crucial
for successful treatment, as with all types of cancer. The pap-smear test is considered the …

Taking into account the limitations of optical imaging, image acquisition equipment is usually
designed to make a trade-off between spatial information and spectral information …

In modern healthcare, the precision of medical image segmentation holds immense
significance for diagnosis and treatment planning. Deep learning techniques, such as …

Medical image fusion has many applications to healthcare that is accomplished by
extracting and then combining the complementary information from multiple medical images …

Accurate lesion segmentation is a critical technology basis for the treatment and prognosis
of stroke. Stroke lesion segmentation suffers from complex background and noise interferes …

Brain tumors have shown extreme mortality and increasing incidence during recent years,
which bring enormous challenges for the timely diagnosis and effective treatment of brain …

Abstract Vision Transformer (ViT) has emerged as a potential alternative to convolutional
neural networks for large datasets. However, applying ViT directly to medical image …