Developing prognostic deep learning models in IPF using OSIC dataset. - Vienna 2024

Emerging imaging techniques in chronic diseases and personalised medicine

Chair(s): ?d?m Domonkos T?rnoki, Helmut Prosch

Session type: Oral presentation

Developing prognostic deep learning models in IPF using OSIC dataset.

Joshua Galanter

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129Xe magnetic resonance imaging for monitoring lung function and microstructure in patients on treatment for progressive fibrosing interstitial lung disease

Agilo Luitger Kern

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Poster

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A novel approach to non-contrast, free-breathing functional lung MRI to generate dynamic measures of ventilation (V) and perfusion (Q).

Zachary Peggs

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Poster

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Developing prognostic deep learning models in IPF using OSIC dataset.

Joshua Galanter

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Poster

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The alterations of pulmonary morphological parameters with aging: an observational study with quantitative computed tomography

Anqi Liu

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Poster

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Quantitative CT measures are sensitive to clinical bronchiectasis severity: preliminary data from the BRILLIANT study

Fran?ois-xavier Bl

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Poster

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Automated computed tomography measures predict functional decline in cystic fibrosis

Gabrielle Baxter

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Poster

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Endobronchial polarization sensitive optical coherence tomography for airway smooth muscle detection in pulmonary disease

Tatiana Soldati

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Poster

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Association between physical activity and imaging biomarker in asthma: An analysis of distributional differences.

Ayumi Fukatsu-chikumoto

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Poster

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Importance of subpleural fibrosis measured by a computer-aided system in patients with interstitial pneumonias, the prospective multicenter study.

Tae Iwasawa

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Discussion and Q&A

CDN Connection Issue

The ERS Congress 2024, Vienna

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