Ultrasound (US) is generally preferred because it is of low-cost, safe, and non-invasive. US
image segmentation is crucial in image analysis. Recently, deep learning-based methods …

Deep-learning models have enabled performance leaps in analysis of high-dimensional
functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for …

Ultrasound (US) technology is a widely utilized for clinical screening owing to its cost-
effectiveness, painlessness, and convenience. However, the automatic segmentation of …

Automated segmentation is a challenging task in medical image analysis that usually
requires a large amount of manually labeled data. However, most current supervised …

Ultrasound (US) has become a widely used imaging modality in clinical practice,
characterized by its rapidly evolving technology, advantages, and unique challenges, such …

KRAS is a pathogenic gene frequently implicated in non-small cell lung cancer (NSCLC).
However, biopsy as a diagnostic method has practical limitations. Therefore, it is important to …

Ultrasound image segmentation deep learning still has performance bottleneck due to an
inherent speckle noise having complex non-Gaussian statistics in the images. Denoised …

Background: Many issues might arise with surgical closure, such as postoperative pain,
sternotomy scar, and postoperative arrhythmias as well as heart block. The purpose of this …