Designed to reduce false positives and shorten the time to diagnosis, the deep learning-based software takes a radiomics approach to assessing lung nodules found on low-dose CT lung screening exams, according to the vendor. RevealAI-Lung generates what the company calls a malignancy similarity index, which is composed of hundreds of CT characteristics that are combined to create a morphological biomarker of malignancy.
The biomarker is then used to compare the nodule being diagnosed with nodules in a reference database that have known diagnostics and outcomes, Mindshare said.
RevealAI-Lung can integrate with a facility's PACS and vendor-neutral archive, the company said.
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