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Radiology of the future- in the press

Home>Radiology of the future- in the press
Radiology of the future- in the pressadmin2020-07-31T07:31:09+00:00
  • CT-based Airway Surface Area to Volume Ratio for Phenotyping Airway Remodeling in Chronic Obstructive Pulmonary Disease | Aug 2020 | American Journal of Respiratory and Critical Care Medicine
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  • Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence | Jul 2020 | Radiology
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  • Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration | Jun 2020 | Acta Ophthalmologica
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  • COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System | May 2020 | Radiology
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  • Five-year Progression of Emphysema and Air Trapping at CT in Smokers with and Those without Chronic Obstructive Pulmonary Disease: Results from the COPDGene Study | Apr 2020 | Rad
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  • Automated chest X-ray reading for tuberculosis in the Philippines to improve case detection: a cohort study | Jul 2019 | The International Journal of Tuberculosis and Lung Disease
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  • Endobronchial valves for severe emphysema | Jun 2019 | European Respiratory Review
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  • A Deep Learning Method to Estimate Conventional Dose Computed Tomography Scans from Reduced Dose Acquisitions: Effect on Emphysema Quantification | May 2019 | American Journal of Respiratory and Critical Care Medicine
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  • A Novel Method for Quantification of Expiratory Airtrapping Independent of Expiration Level | May 2019 | American Journal of Respiratory and Critical Care Medicine
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  • Genetic risk score has added value over initial clinical grading stage in predicting disease progression in age-related macular degeneration | Apr 2019 | Nature Scientific reports
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In the press

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Goals and Results

GOALS 

Quantitative analysis of medical images plays a substantial role in research and clinical trials. Thirona’s lung quantification software offers analysis of chest CT scans based on artificial intelligence, aiding in the detection, evaluation, and treatment planning of lung diseases. Analysis provided by the software include quantifications of anatomical volumes, disease distributions, airway morphology, vascular morphology, and fissure completeness.

Goal 1: work together

Data from over 300 hospitals worldwide is processed on a daily basis.

Goal 2: work with everyone

Thirona’s quantitative analysis is widely used in scientific research.

Goal 3: work with the universe

We use the latest deep learning techniques.

Analyses

Quirem

Our strong scientific heritage and embedding enable us to continuously innovate using the latest developments in artificial intelligence. Current development areas include bronchiectasis and mucous quantification in Cystic Fibrosis, quantification of the pulmonary arteries and veins, CT-approximated perfusion and ventilation quantification in COPD, detection of interstitial lung disease patterns, and sublobar segmentation.

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