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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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Updated: 8/28/2025
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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
Ultra Low-Dose CT Image-Guided Intervention Using Previous Scans as Prior Constraints
System and methodology of performing low-dose CT images directly correlated with lowering the mAs parameter in data acquisition Background: It is well documented that the more X-ray CT imaging exposure time in a clinic, the more harm is caused to the patient. Low-dose CT is desirable in numerous clinical applications. Technology Overview: Low-dose...
Published: 9/6/2024
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Updated: 8/27/2020
|
Inventor(s):
Jerome Liang
,
Jianhua Ma
,
Hao Zhang
,
William Moore
,
Hao Han
Keywords(s):
Image-Guided Intervention
,
Previous Normal-Dose Prior
,
Technologies
,
Ultra Low-Dose CT
Category(s):
Campus > Stony Brook University
,
Technology Classifications > Medical Devices
,
Technology Classifications > Research Tools and Reagents