Machine Learning Diagnosis of In Vivo Tissues by Extracting Tissue-Energy Characteristic Features from Non-Invasively Acquired Computed Tomographic Data
The technology features enable ML models to more accurately classify indeterminate pulmonary nodules and colorectal polyps
Background:
Computed tomography (CT) is a widely used imaging tool for early detection of cancers such as lung and colorectal cancer. However, current low-dose CT screening protocols suffer from high false positive rates, particularly...
Published: 7/14/2026
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Inventor(s): Jerome Liang, Shaojie Chang, Weiguo Cao, Yongfeng Gao, Marc Pomeroy, Licheng Kuo
Keywords(s):
Category(s): Technology Classifications > Artificial Intelligence, Technology Classifications > Computer Software, Technology Classifications > Diagnostics, Technology Classifications > Healthcare IT, Technology Classifications > Information Technology, Technology Classifications > Medical Imaging, Campus > Stony Brook University
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