1 citations · 1 across the 3 of their papers we have counts for
3 papers
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans
Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali +6
Consistent segmentation of COVID-19 patient's CT scans across multiple time points is essential to assess disease progression and response to therapy accurately. Existing automatic…
Generating Unrestricted Adversarial Examples via Three Parameters
Hanieh Naderi, Leili Goli, Shohreh Kasaei
Deep neural networks have been shown to be vulnerable to adversarial examples deliberately constructed to misclassify victim models. As most adversarial examples have restricted th…
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs
Seong Tae Kim, Leili Goli, Magdalini Paschali +7
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 a…