Abstract: Tumor segmentation is crucial for surgical planning and precise tumor resection for effective treatment. Traditionally, tumor localization has been performed using medical imaging techniques ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

Introduction: Quantifying adiposity, a key biomarker of metabolic health, typically requires imaging that involves radiation, high costs, and manual effort. We developed an AI framework to segment ...

For startups and established businesses, understanding the importance of segmentation is essential for the granular analysis of consumer demographics, behaviors, needs, and preferences. These insights ...

Students call it hypocritical. A senior at Northeastern University demanded her tuition back. But instructors say generative A.I. tools make them better at their jobs. By Kashmir Hill In February, ...

Brain tumor segmentation from Magnetic Resonance Images (MRI) presents significant challenges due to the complex nature of brain tumor tissues. This complexity poses a significant challenge in ...

Good businesses know that customer segmentation is a necessity. It’s used for everything from market strategies to discount offers to developing loyalty programs. The more accurate the segmentation is ...

X-ray phase-contrast micro computed tomography using synchrotron radiation (SR PhC-µCT) offers unique 3D imaging capabilities for visualizing microstructure of the human brain. Its applicability for ...