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Longitudinal quantitative assessment of covid-19 infection progression from chest CTs
, Article 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, 27 September 2021 through 1 October 2021 ; Volume 12907 LNCS , 2021 , Pages 273-282 ; 03029743 (ISSN); 9783030872335 (ISBN) ; Goli, L ; Paschali, M ; Khakzar, A ; Keicher, M ; Czempiel, T ; Burian, E ; Braren, R ; Navab, N ; Wendler, T ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2021
Abstract
Chest computed tomography (CT) has played an essential diagnostic role in assessing patients with COVID-19 by showing disease-specific image features such as ground-glass opacity and consolidation. Image segmentation methods have proven to help quantify the disease and even help predict the outcome. The availability of longitudinal CT series may also result in an efficient and effective method to reliably assess the progression of COVID-19, monitor the healing process and the response to different therapeutic strategies. In this paper, we propose a new framework to identify infection at a voxel level (identification of healthy lung, consolidation, and ground-glass opacity) and visualize the...