1 code implementation • 4 Dec 2023 • Diedre S. Carmo, Jean A. Ribeiro, Alejandro P. Comellas, Joseph M. Reinhardt, Sarah E. Gerard, Letícia Rittner, Roberto A. Lotufo
The COVID-19 pandemic response highlighted the potential of deep learning methods in facilitating the diagnosis, prognosis and understanding of lung diseases through automated segmentation of pulmonary structures and lesions in chest computed tomography (CT).
1 code implementation • 13 Oct 2023 • Diedre S. Carmo, Rosarie A. Tudas, Alejandro P. Comellas, Leticia Rittner, Roberto A. Lotufo, Joseph M. Reinhardt, Sarah E. Gerard
A comprehensive ablation study was performed to evaluate the contribution of the proposed network modifications.
no code implementations • 6 Oct 2022 • Muhammad F. A. Chaudhary, Sarah E. Gerard, Gary E. Christensen, Christopher B. Cooper, Joyce D. Schroeder, Eric A. Hoffman, Joseph M. Reinhardt
To assess model generalizability beyond the development set biases, we evaluate our model on an out-of-distribution external validation set of 200 subjects.
no code implementations • 15 Oct 2021 • Muhammad F. A. Chaudhary, Sarah E. Gerard, Di Wang, Gary E. Christensen, Christopher B. Cooper, Joyce D. Schroeder, Eric A. Hoffman, Joseph M. Reinhardt
Once trained, the framework can be used as a registration-free method for predicting local tissue expansion.
no code implementations • 16 Oct 2020 • Sarah E. Gerard, Jacob Herrmann, Yi Xin, Kevin T. Martin, Emanuele Rezoagli, Davide Ippolito, Giacomo Bellani, Maurizio Cereda, Junfeng Guo, Eric A. Hoffman, David W. Kaczka, Joseph M. Reinhardt
Regional lobar analysis was performed using hierarchical clustering to identify radiographic subtypes of COVID-19.