Of the many feats achieved by artificial intelligence (AI), the ability to process images quickly and accurately has had an ...

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...

There is an emerging convergence between atherosclerotic cardiovascular disease and cancer, driven by shared risk factors and overlapping pathophysiologic mechanisms. Traditional factors, such as ...

Satellite imaging is the technology that offer real-time geospatial information in the form of images. These images are further utilized across various applications for commercial purposes. The ...

In 2025, North America held a dominan market position, capturing more than a 38.6% share, holding USD 0.64 Billion revenue.

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Numerous challenges, including the variable anatomy of SC, ...

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning. In disciplines like ...

Introduction: The choroid plexus (CP), a critical structure for cerebrospinal fluid (CSF) production, has been increasingly recognized for its involvement in Alzheimer’s disease (AD). Accurate ...

The segmentation and classification of breast ultrasound (BUS) images are crucial for the early diagnosis of breast cancer and remain a key focus in BUS image processing. Numerous machine learning and ...