Medico-visual processing is a rapidly expanding and significant field right now. A number of
modules, including X-ray, ultrasound, MRI, CAT, PET, SPECT, and BIOPSY, are used to get …

Abstract Unsupervised Domain Adaptation (UDA) is a promising strategy for representing
unlabeled data through domain alignment. Nonetheless, a considerable number of whole …

Due to more advancements in deep learning approaches, medical image analysis has
become more popular in research. Image segmentation plays an indispensable role in …

Accurate medical image segmentation is an essential part of the medical image analysis
process that provides detailed quantitative metrics. In recent years, extensions of classical …

Medical image segmentation is an essential process to assist clinics with computer-aided
diagnosis and treatment. Recently, a large amount of convolutional neural network (CNN) …

Contrastive learning, as an unsupervised technique, is widely employed in image
segmentation to enhance segmentation performance even when working with small labeled …

Medical imaging is a dynamic domain where new acquisition protocols are regularly
developed and employed to meet changing clinical needs. Deep learning models for …

Skin lesion segmentation from thermoscopic images is crucial for better quantitative
melanoma analysis. However, it is still demanding because of the skin lesions' large-scale …

Purpose: To analyze the development process of artificial intelligence applied to ultrasound
medicine in these 6 years and to provide a reliable forecast of future trends. Methods: We …