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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
  • Automated grading of fundus photographs to identify referable AMD for first-line eye care | Nov 2017 | JAMA Ophthalmology
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  • Fast interactive segmentation of the pulmonary lobes from thoracic computed tomography data | May 2017 | Physics in Medicine and Biology
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  • Automatic versus human reading of chest X-rays in the Zambia National Tuberculosis Prevalence Survey | Feb 2017 | International Journal of Tuberculosis and Lung Disease
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  • Improving airway segmentation in computed tomography using leak detection with convolutional networks | Feb 2017 | Medical Image Analysis
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  • Automatic Pulmonary Artery-Vein Separation and Classification in Computed Tomography Using Tree Partitioning and Peripheral Vessel Matching | Oct 2016 | IEEE Transactions on Medical Imaging
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  • An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information | Aug 2016 | Nature Scientific Reports
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  • Follow-up of CT-derived airway wall thickness: Correcting for changes in inspiration level improves reliability | Jun 2016 | European Journal of Radiology
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  • Genetic association analysis of drusen progression | Apr 2016 | Investigative Ophthalmology and Visual Science
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  • Automatic Segmentation of Drusen and Exudates on Color Fundus Images using Generative Adversarial Networks | Mar 2016 | Biomedical Optics Express
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  • Fast convolutional neural network training using selective data sampling: Application to hemorrhage detection in color fundus images | Feb 2016 | IEEE Transactions on Medical Imaging
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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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