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Analyzes chronic obstructive pulmonary disease on chest CT images with deep learning AI technology
Aview:COPD performs automatically pre-processing in lungs, lung lobes, and airway and quantitatively analyzes chronic obstructive pulmonary disease. A report with detailed results is automatically generated. Clearly classify and analyze phenotypes of chronic obstructive pulmonary disease.
Applications and diseases
During: perception aid (prompting all abnormalities/results/heatmaps), During: interactive decision support (shows abnormalities/results only on demand), During: report suggestion.
Lung lobe segmentation, Low Attenuation Analysis (LAA), Emphysema, Vessel Analysis, Fissure Integrity, Airway Measurements, Pulmonary Vessels.
Detectable pathologies
Advantages
- Rapid auto-segmentation process of lungs, lobes, airways, etc.
- It analyzes the phenotype for COPD and shows the results in charts and graphs (LAA analysis, Emphysema cluster size analysis, Fissure analysis, Airway analysis and Lung vessel analysis).
- It is possible to conduct the radiomics research on the pulmonary function with the quantitatively calculated and comprehensively extracted bio-indicators.
References
Heejun Park, MS, Jaeyoun Yi, PhD, Donghoon Yu MS, Hyungi Seo MS, Jongha Park, MS, Jihye Yun, PhD, Namkug Kim, PhD, Sang Min Lee A, MD, Sang Min Lee B, MD, Joon Beom Seo, MD, PhD, “Fully Automated Workflow for Advanced Quantitative Analysis on Multi-Volume Chest CT of Patients with Chronic Obstructive Pulmonary Disease using Deep Convolutional Neural Net and Conventional Image Processing” RSNA2018, Chicago IL.
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