Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

Segmentation is essential for medical image analysis to identify and localize diseases,
monitor morphological changes, and extract discriminative features for further diagnosis …

Skin lesion segmentation is a fundamental procedure in computer-aided melanoma
diagnosis. However, due to the diverse shape, variable size, blurry boundary, and noise …

Medical image segmentation is an essential task in computer-aided diagnosis. Despite their
prevalence and success, deep convolutional neural networks (DCNNs) still need to be …

Convolutional neural networks (CNN) are sensitive to domain shifts, which can result in poor
generalization. In medical imaging, data acquisition conditions differ among institutions …

Considerable research and surveys indicate that skin lesions are an early symptom of skin
cancer. Segmentation of skin lesions is still a hot research topic. Dermatological datasets in …

Image segmentation of polyps can provide an important basis for the diagnosis of colorectal
cancer and has a high clinical application value. Segmentation of polyp regions is very …

Abstract Recently emerged SAM-Med2D represents a state-of-the-art advancement in
medical image segmentation. Through fine-tuning the Large Visual Model, Segment …

BACKGROUND: Medical image processing has gained much attention in developing
computer-aided diagnosis (CAD) of diseases. CAD systems require deep understanding of …