RadNet’s AI solution for lung nodule detection and management, Veye Lung Nodules, is developed by Aidence, a RadNet subsidiary and a leading innovator in radiology AI and machine learning.

Customers in seven countries rely on Aidence AI technology, including the National Health Service in the U.K. In its mission to improve lung cancer prognosis, the NHS uses Aidence AI for large-scale population screening.

Veye Lung Nodules assists radiologists with all the time-consuming counting, measuring, and segmenting of lesions.

  • Automated volumetry for insights on the evolution of a nodule.

  • No workflow change—no additional login or clicks.

  • Support for detection, quantification, growth assessment, and classification.

  • An average 40% reduction in reading time and higher reading agreement when using Veye.

The Netherlands Cancer Institute, one of the world’s top 10 comprehensive cancer centers, is using Veye Lung Nodules in their cancer clinic.

Google and Aidence

Proper identification and diagnosis of detected lung nodules can be time-consuming, costly, and sometimes invasive. Deep learning has been shown to improve malignancy classification, and Aidence recently teamed with Google Health to develop a lung nodule malignancy prediction model. The goal is to accelerate and expand the impact in clinical practice, bringing the highest-quality care to lung cancer patients.

Florida Lung Health Coalition

RadNet is teaming with the Florida Lung Health Coalition to accelerate the uptake and adherence of lung disease screening in Florida. RadNet will leverage its state-of-the-art AI technology to help drive more accurate and early detection.

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To learn more about RadNet’s AI solution for lung health screening, click here.