In the talk Helmut Prosch and Georg Langs will discuss the role of deep learning and image based search in the context of lung CT diagnosis. Faced with
In the talk Helmut Prosch and Georg Langs will discuss the role of deep learning and image based search in the context of lung CT diagnosis. Faced with complex diagnostic assessment of lung diseases such as lung fibrosis, the computational quantification of disease patterns, and the search for similar cases can help assessing individual cases. Quantitative profiles turn imaging data into signatures that can enter treatment decisions. Image based search enables the comparison of CT images with known findings to help recognising tissue changes, and perform reliable differential diagnosis. The talk will illustrate the challenges of diagnosing fibrosing lung diseases, and the practical impact of machine learning in radiological practice.
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(Monday) 19:00 - 20:00
EuSoMIIprinaldi.email@example.com Am Gestade 1 - 1010 Vienna, Austria
Speakers for this event
Georg Langs is the Head of the Computational Image Analysis and Radiology Lab (CIR) at the Medical University of Vienna. He also is a Co-Founder and Chief Scientist at contextflow and reviews for several conferences and journals, among them IEEE Transactions on Pattern Recognition and Machine Intelligence and IEEE Transactions on Medical Imaging.
Helmut Prosch is an Associate Professor of Radiology and Section Chief of Thoracic Imaging at the Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna. He has published more than 100 articles, reviews and book chapters, and his research focuses on diagnosis and staging of lung cancer and deep learning for the diagnosis of diffuse parenchymal lung diseases.