Background: The accurate separation of lung parenchyma, ground-glass opacity (GGO), and intrapulmonary vessels on high-resolution computed tomography (HRCT) in coronavirus disease 2019 (COVID-19) is ...

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 ...

Dr. McBain studies policies and technologies that serve vulnerable populations. On any given night, countless teenagers confide in artificial intelligence chatbots — sharing their loneliness, anxiety ...

Anatomical structure segmentation and analysis in CT images. Body-region segmentation and detection in CT scans. X-ray image segmentation Figure 1: Standard CT workflow. Volumetric scans and ...

Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...

Warning: Unable to import some ONNX operators, because they are not supported. They have been replaced by placeholder layers or by placeholder functions inside generated custom layers. To find the ...

Abstract: This paper addresses the challenge of segmenting the epicardial adipose tissue (EAT) in MRI scans, a critical aspect in cardiac-related clinical diagnosis, treatment, and evaluation of ...

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 ...