Consolidated efforts have been made to enhance the treatment and diagnosis of heart
disease due to its detrimental effects on society. As technology and medical diagnostics …

Accurate and automatic segmentation of medical images is a key step in clinical diagnosis
and analysis. Currently, the successful application of Transformers' model in the field of …

Accurate segmentation of medical images is crucial for clinical diagnosis and evaluation.
However, medical images have complex shapes, the structures of different objects are very …

During the past three years, the coronavirus disease 2019 (COVID-19) has swept the world.
The rapid and accurate recognition of covid-19 pneumonia are, therefore, of great …

Background and objective: Gland segmentation of pathological images is an essential but
challenging step for adenocarcinoma diagnosis. Although deep learning methods have …

Convolution operation is performed within a local window of the input image. Therefore,
convolutional neural network (CNN) is skilled in obtaining local information. Meanwhile, the …

Colorectal cancer (CRC) has been one of the top three disease in the world in terms of
incidence for many years. Therefore, how to prevent and treat CRC has become a topic of …

Medical image segmentation plays a crucial role in clinical assistance for diagnosis. The
UNet-based network architecture has achieved tremendous success in the field of medical …

Accurate segmentation of tubular structures, such as blood vessels and bile ducts, is pivotal
for clinical diagnosis and subsequent treatment. However, challenges arise from their …

Accurate segmentation of skin lesions within dermoscopic images plays a crucial role in the
timely identification of skin cancer for computer-aided diagnosis on mobile platforms …