Background Alexander disease is an autosomal dominant leukodystrophy caused by heterozygous pathogenic variants in the glial ...

Under the business model Fujitsu Uvance, Fujitsu is building an ecosystem of Uvance Partners that will apply data and AI ...

In a significant milestone for global healthcare innovation, the World Health Organization (WHO) has released a technical ...

Introduction to Computer Vision in HealthcareLet’s face it—healthcare can be slow, expensive, and prone to human error. But what if a camera and some smart algorithms could help change that? That's ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

The global Medical Imaging Market is valued at USD 41.62 Billion in 2024 and is projected to reach a value of USD 71.88 ...

Vivian Health reports AI is revolutionizing medical imaging, enhancing speed, accuracy, and patient care through advanced algorithms and FDA clearances.

Explore how AI-driven Smart Diagnostics are revolutionizing healthcare, as the market shifts from research to clinical practice. Discover the potential for premium diagnostics, pricing trends, and ...

Advanced robotic vision systems are redefining the capabilities of automation in performing precision tasks. By equipping robots with the ability to perceive and adapt to their environments, these ...

Woese Institute for Genomic Biology are a step closer to realizing this goal by integrating machine learning-based analysis into point-of-care biosensing technologies. The new method, ...

More information: Yuqiao Yang et al, Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography, IEEE Access (2025).

The integration of deep learning in neuroimaging enhances diagnostic capabilities, offering new insights into neurological disorders and treatment responses.