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Artificial Intelligent Image Processing and Diagnosis of Pulmonary Vessels in CT
Sponsor: Xin Lou
Summary
In this study, patients with chest pain, lung cancer, pulmonary embolism, and routine inpatient physical examination were selected as the research objects, and the experimental design of retrospective cohort study was adopted to carry out artificial intelligence analysis related to pulmonary vascular diseases in patients with multi-dimensional big data. The multi-modal CT acquisition process included plain scan CT(NCCT) and CT pulmonary angiography (CTPA). Ctpa-like image effects can be simulated or reconstructed by non-enhanced plain scan CT images, so that CTPA-like image quality can be obtained without injecting contrast agent. The synthetic CTPA images were further analyzed by artificial intelligence to assist doctors in the intelligent diagnosis of pulmonary vascular diseases.
Key Details
Gender
All
Age Range
18 Years - 100 Years
Study Type
OBSERVATIONAL
Enrollment
15000
Start Date
2024-09-10
Completion Date
2029-09-01
Last Updated
2024-09-19
Healthy Volunteers
No
Conditions
Interventions
Deep learning imaging enhancement
Conventional imaging or down-sampling imaging from CT or MR are enhanced by approved deep learning method.