no code implementations • 11 Dec 2019 • Rhona Asgari, Sebastian Waldstein, Ferdinand Schlanitz, Magdalena Baratsits, Ursula Schmidt-Erfurth, Hrvoje Bogunović
In the second approach, the surrounding retinal layers (outer boundary retinal pigment epithelium (OBRPE) and Bruch's membrane (BM)) are segmented and the remaining space between these two layers is extracted as drusen.
no code implementations • 18 Jun 2019 • Rhona Asgari, José Ignacio Orlando, Sebastian Waldstein, Ferdinand Schlanitz, Magdalena Baratsits, Ursula Schmidt-Erfurth, Hrvoje Bogunović
We also introduce connections between each class-specific branch and the additional decoder to increase the regularization effect of this surrogate task.
no code implementations • 24 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.
no code implementations • 23 Jan 2019 • José Ignacio Orlando, Philipp Seeböck, Hrvoje Bogunović, Sophie Klimscha, Christoph Grechenig, Sebastian Waldstein, Bianca S. Gerendas, Ursula Schmidt-Erfurth
In this paper, we introduce a Bayesian deep learning based model for segmenting the photoreceptor layer in pathological OCT scans.
Ranked #4 on Image Matting on AIM-500
no code implementations • 2 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.