To our knowledge, this study is the first to apply deep learning models that can, beyond diagnosis, identify molecular subtypes and predict outcomes in a single brain tumour entity (meningioma) using ...

The aim of this study was to evaluate the performance of an artificial intelligence (AI)–based method for automated ...

Explore the ultimate guide to automated brain organoid culture workflows and learn how the CellXpress.ai system enables scalable ...

Pediatric oncology is rapidly advancing through precision therapeutics, biomarker-informed trials, and adaptive treatment strategies designed to improve ...

Millions of people are diagnosed with Alzheimer's disease each year, comprising 60% to 70% of dementia cases worldwide. While cognitive impairment and structural brain changes are indicative of ...

Abstract: Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video ...

In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a pivotal role, which impacts the diagnosis and treatment of conditions such as endocrine dysfunctions and visual ...

Abstract: We describe a method for verifying the output of a deep neural network for medical image segmentation that is robust to several classes of random as well as worst-case perturbations i.e.

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Computer Vision (CV) has evolved rapidly ...

Deep learning, an advanced artificial intelligence technique, has become increasingly popular in the past few years, thanks to abundant data and increased computing power. It's the main technology ...

Medical image segmentation based on deep learning has become a powerful tool in the field of medical image processing. Due to the special nature of medical images, image segmentation algorithms based ...