26 citations · 27 across the 3 of their papers we have counts for
4 papers
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data
Dmitrii Lachinov, Arunava Chakravarty, Christoph Grechenig +2
Robust forecasting of the future anatomical changes inflicted by an ongoing disease is an extremely challenging task that is out of grasp even for experienced healthcare profession…
Segmentation of Bruch's Membrane in retinal OCT with AMD using anatomical priors and uncertainty quantification
Botond Fazekas, Dmitrii Lachinov, Guilherme Aresta +3
Bruch's membrane (BM) segmentation on optical coherence tomography (OCT) is a pivotal step for the diagnosis and follow-up of age-related macular degeneration (AMD), one of the lea…
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
Dmitrii Lachinov, Philipp Seeboeck, Julia Mai +2
In medical imaging, there are clinically relevant segmentation tasks where the output mask is a projection to a subset of input image dimensions. In this work, we propose a novel c…
On orthogonal projections for dimension reduction and applications in augmented target loss functions for learning problems
Anna Breger, Jose Ignacio Orlando, Pavol Harar +6
The use of orthogonal projections on high-dimensional input and target data in learning frameworks is studied. First, we investigate the relations between two standard objectives i…