3 papers
cs.CV2024
Robust deep labeling of radiological emphysema subtypes using squeeze and excitation convolutional neural networks: The MESA Lung and SPIROMICS Studies
Artur Wysoczanski, Nabil Ettehadi, Soroush Arabshahi +10
Pulmonary emphysema, the progressive, irreversible loss of lung tissue, is conventionally categorized into three subtypes identifiable on pathology and on lung computed tomography…
eess.IV2023
MEDPSeg: Hierarchical polymorphic multitask learning for the segmentation of ground-glass opacities, consolidation, and pulmonary structures on computed tomography
Diedre S. Carmo, Jean A. Ribeiro, Alejandro P. Comellas +4
The COVID-19 pandemic response highlighted the potential of deep learning methods in facilitating the diagnosis, prognosis and understanding of lung diseases through automated segm…
eess.IV2023
Automatic segmentation of lung findings in CT and application to Long COVID
Diedre S. Carmo, Rosarie A. Tudas, Alejandro P. Comellas +4
Automated segmentation of lung abnormalities in computed tomography is an important step for diagnosing and characterizing lung disease. In this work, we improve upon a previous me…