93 citations · 145 across the 6 of their papers we have counts for
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eess.IV2020★ 3 cited
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging
Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky +37
Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised c…
eess.IV2020★ 14 cited
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
Sofie Tilborghs, Ine Dirks, Lucas Fidon +19
Recent research on COVID-19 suggests that CT imaging provides useful information to assess disease progression and assist diagnosis, in addition to help understanding the disease.…