Search Results for author: Philipp Seeböck

Found 7 papers, 1 papers with code

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT

no code implementations29 May 2019 Philipp Seeböck, José Ignacio Orlando, Thomas Schlegl, Sebastian M. Waldstein, Hrvoje Bogunović, Sophie Klimscha, Georg Langs, Ursula Schmidt-Erfurth

We propose to take advantage of this property using bayesian deep learning, based on the assumption that epistemic uncertainties will correlate with anatomical deviations from a normal training set.

Anatomy Anomaly Detection

Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation

no code implementations24 Jan 2019 Philipp Seeböck, David Romo-Bucheli, Sebastian Waldstein, Hrvoje Bogunović, José Ignacio Orlando, Bianca S. Gerendas, Georg Langs, Ursula Schmidt-Erfurth

Among the several sources of variability the ML models have to deal with, a major factor is the acquisition device, which can limit the ML model's generalizability.

Identifying and Categorizing Anomalies in Retinal Imaging Data

no code implementations2 Dec 2016 Philipp Seeböck, Sebastian Waldstein, Sophie Klimscha, Bianca S. Gerendas, René Donner, Thomas Schlegl, Ursula Schmidt-Erfurth, Georg Langs

The identification and quantification of markers in medical images is critical for diagnosis, prognosis and management of patients in clinical practice.

Clustering Management

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