Quantitative Assessment of Chest CT Patterns in COVID-19 and Bacterial Pneumonia Patients: a Deep Learning Perspective.
Myeongkyun KangKyung Soo HongPhilip ChikontweMiguel LunaJong Geol JangJong Soo ParkKyeong Cheol ShinSang Hyun ParkJune Hong AhnPublished in: Journal of Korean medical science (2021)
Deep chest CT analysis with constructed lesion clusters revealed well-known COVID-19 CT manifestations comparable to manual CT analysis. The constructed histogram features improved accuracy for both diseases and severity classification, and showed correlations with laboratory data and clinical parameters. The constructed histogram features can provide guidance for improved analysis and treatment of COVID-19.
Keyphrases
- coronavirus disease
- contrast enhanced
- sars cov
- deep learning
- computed tomography
- image quality
- wastewater treatment
- machine learning
- positron emission tomography
- end stage renal disease
- newly diagnosed
- ejection fraction
- extracorporeal membrane oxygenation
- mechanical ventilation
- patient reported outcomes
- respiratory syndrome coronavirus
- acute respiratory distress syndrome
- pet ct
- data analysis
- respiratory failure