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eess.IV2021★ 1 cited
Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT
Simone Bendazzoli, Irene Brusini, Mehdi Astaraki +7
Segmentation of COVID-19 lesions from chest CT scans is of great importance for better diagnosing the disease and investigating its extent. However, manual segmentation can be very…
eess.IV2020★ 3 cited
A deep learning-based pipeline for error detection and quality control of brain MRI segmentation results
Irene Brusini, Daniel Ferreira Padilla, José Barroso +4
Brain MRI segmentation results should always undergo a quality control (QC) process, since automatic segmentation tools can be prone to errors. In this work, we propose two deep le…