172 citations · 322 across the 4 of their papers we have counts for
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U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography
Rhona Asgari, Sebastian Waldstein, Ferdinand Schlanitz +3
The presence of drusen is the main hallmark of early/intermediate age-related macular degeneration (AMD). Therefore, automated drusen segmentation is an important step in image-gui…
Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning
Antoine Rivail, Ursula Schmidt-Erfurth, Wolf-Dieter Vogl +5
Longitudinal imaging is capable of capturing the static ana\-to\-mi\-cal structures and the dynamic changes of the morphology resulting from aging or disease progression. Self-supe…
Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography
Rhona Asgari, José Ignacio Orlando, Sebastian Waldstein +4
Automated drusen segmentation in retinal optical coherence tomography (OCT) scans is relevant for understanding age-related macular degeneration (AMD) risk and progression. This ta…
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
Philipp Seeböck, José Ignacio Orlando, Thomas Schlegl +5
Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical images. Although supervised deep learning can perform accurate segmentation of pathological a…